| Records |
| Author |
Mathieu Nicolas Delalandre; Jean-Yves Ramel; Ernest Valveny; Muhammad Muzzamil Luqman |
| Title |
A Performance Characterization Algorithm for Symbol Localization |
Type |
Book Chapter |
| Year |
2010 |
Publication |
Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers |
Abbreviated Journal |
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| Volume |
6020 |
Issue |
|
Pages |
260–271 |
| Keywords |
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| Abstract |
In this paper we present an algorithm for performance characterization of symbol localization systems. This algorithm is aimed to be a more “reliable” and “open” solution to characterize the performance. To achieve that, it exploits only single points as the result of localization and offers the possibility to reconsider the localization results provided by a system. We use the information about context in groundtruth, and overall localization results, to detect the ambiguous localization results. A probability score is computed for each matching between a localization point and a groundtruth region, depending on the spatial distribution of the other regions in the groundtruth. Final characterization is given with detection rate/probability score plots, describing the sets of possible interpretations of the localization results, according to a given confidence rate. We present experimentation details along with the results for the symbol localization system of [1], exploiting a synthetic dataset of architectural floorplans and electrical diagrams (composed of 200 images and 3861 symbols). |
| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
LNCS |
| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN  |
978-3-642-13727-3 |
Medium |
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| Area |
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Expedition |
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Conference |
GREC |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ DRV2010 |
Serial |
2406 |
| Permanent link to this record |
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| |
| Author |
Marçal Rusiñol; K. Bertet; Jean-Marc Ogier; Josep Llados |
| Title |
Symbol Recognition Using a Concept Lattice of Graphical Patterns |
Type |
Book Chapter |
| Year |
2010 |
Publication |
Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers |
Abbreviated Journal |
|
| Volume |
6020 |
Issue |
|
Pages |
187-198 |
| Keywords |
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| Abstract |
In this paper we propose a new approach to recognize symbols by the use of a concept lattice. We propose to build a concept lattice in terms of graphical patterns. Each model symbol is decomposed in a set of composing graphical patterns taken as primitives. Each one of these primitives is described by boundary moment invariants. The obtained concept lattice relates which symbolic patterns compose a given graphical symbol. A Hasse diagram is derived from the context and is used to recognize symbols affected by noise. We present some preliminary results over a variation of the dataset of symbols from the GREC 2005 symbol recognition contest. |
| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
LNCS |
| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-642-13727-3 |
Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ RBO2010 |
Serial |
2407 |
| Permanent link to this record |
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| |
| Author |
Partha Pratim Roy; Umapada Pal; Josep Llados |
| Title |
Touching Text Character Localization in Graphical Documents using SIFT |
Type |
Book Chapter |
| Year |
2010 |
Publication |
Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers |
Abbreviated Journal |
|
| Volume |
6020 |
Issue |
|
Pages |
199-211 |
| Keywords |
Support Vector Machine; Text Component; Graphical Line; Document Image; Scale Invariant Feature Transform |
| Abstract |
Interpretation of graphical document images is a challenging task as it requires proper understanding of text/graphics symbols present in such documents. Difficulties arise in graphical document recognition when text and symbol overlapped/touched. Intersection of text and symbols with graphical lines and curves occur frequently in graphical documents and hence separation of such symbols is very difficult.
Several pattern recognition and classification techniques exist to recognize isolated text/symbol. But, the touching/overlapping text and symbol recognition has not yet been dealt successfully. An interesting technique, Scale Invariant Feature Transform (SIFT), originally devised for object recognition can take care of overlapping problems. Even if SIFT features have emerged as a very powerful object descriptors, their employment in graphical documents context has not been investigated much. In this paper we present the adaptation of the SIFT approach in the context of text character localization (spotting) in graphical documents. We evaluate the applicability of this technique in such documents and discuss the scope of improvement by combining some state-of-the-art approaches. |
| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
LNCS |
| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-642-13727-3 |
Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ RPL2010c |
Serial |
2408 |
| Permanent link to this record |
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| |
| Author |
Susana Alvarez; Anna Salvatella; Maria Vanrell; Xavier Otazu |
| Title |
3D Texton Spaces for color-texture retrieval |
Type |
Conference Article |
| Year |
2010 |
Publication |
7th International Conference on Image Analysis and Recognition |
Abbreviated Journal |
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| Volume |
6111 |
Issue |
|
Pages |
354–363 |
| Keywords |
|
| Abstract |
Color and texture are visual cues of different nature, their integration in an useful visual descriptor is not an easy problem. One way to combine both features is to compute spatial texture descriptors independently on each color channel. Another way is to do the integration at the descriptor level. In this case the problem of normalizing both cues arises. In this paper we solve the latest problem by fusing color and texture through distances in texton spaces. Textons are the attributes of image blobs and they are responsible for texture discrimination as defined in Julesz’s Texton theory. We describe them in two low-dimensional and uniform spaces, namely, shape and color. The dissimilarity between color texture images is computed by combining the distances in these two spaces. Following this approach, we propose our TCD descriptor which outperforms current state of art methods in the two different approaches mentioned above, early combination with LBP and late combination with MPEG-7. This is done on an image retrieval experiment over a highly diverse texture dataset from Corel. |
| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
A.C. Campilho and M.S. Kamel |
| Language |
|
Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
LNCS |
| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-642-13771-6 |
Medium |
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| Area |
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Expedition |
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Conference |
ICIAR |
| Notes |
CIC |
Approved |
no |
| Call Number |
CAT @ cat @ ASV2010a |
Serial |
1325 |
| Permanent link to this record |
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| |
| Author |
Naveen Onkarappa; Angel Sappa |
| Title |
On-Board Monocular Vision System Pose Estimation through a Dense Optical Flow |
Type |
Conference Article |
| Year |
2010 |
Publication |
7th International Conference on Image Analysis and Recognition |
Abbreviated Journal |
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| Volume |
6111 |
Issue |
|
Pages |
230-239 |
| Keywords |
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| Abstract |
This paper presents a robust technique for estimating on-board monocular vision system pose. The proposed approach is based on a dense optical flow that is robust against shadows, reflections and illumination changes. A RANSAC based scheme is used to cope with the outliers in the optical flow. The proposed technique is intended to be used in driver assistance systems for applications such as obstacle or pedestrian detection. Experimental results on different scenarios, both from synthetic and real sequences, shows usefulness of the proposed approach. |
| Address |
Povoa de Varzim (Portugal) |
| Corporate Author |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
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| Language |
|
Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
LNCS |
| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-642-13771-6 |
Medium |
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| Area |
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Expedition |
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Conference |
ICIAR |
| Notes |
ADAS |
Approved |
no |
| Call Number |
ADAS @ adas @ OnS2010 |
Serial |
1342 |
| Permanent link to this record |
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| |
| Author |
Wenjuan Gong; Andrew Bagdanov; Xavier Roca; Jordi Gonzalez |
| Title |
Automatic Key Pose Selection for 3D Human Action Recognition |
Type |
Conference Article |
| Year |
2010 |
Publication |
6th International Conference on Articulated Motion and Deformable Objects |
Abbreviated Journal |
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| Volume |
6169 |
Issue |
|
Pages |
290–299 |
| Keywords |
|
| Abstract |
This article describes a novel approach to the modeling of human actions in 3D. The method we propose is based on a “bag of poses” model that represents human actions as histograms of key-pose occurrences over the course of a video sequence. Actions are first represented as 3D poses using a sequence of 36 direction cosines corresponding to the angles 12 joints form with the world coordinate frame in an articulated human body model. These pose representations are then projected to three-dimensional, action-specific principal eigenspaces which we refer to as aSpaces. We introduce a method for key-pose selection based on a local-motion energy optimization criterion and we show that this method is more stable and more resistant to noisy data than other key-poses selection criteria for action recognition. |
| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
Springer Verlag |
Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-642-14060-0 |
Medium |
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| Area |
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Expedition |
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Conference |
AMDO |
| Notes |
ISE |
Approved |
no |
| Call Number |
DAG @ dag @ GBR2010 |
Serial |
1317 |
| Permanent link to this record |
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| |
| Author |
Jaume Gibert; Ernest Valveny |
| Title |
Graph Embedding based on Nodes Attributes Representatives and a Graph of Words Representation. |
Type |
Conference Article |
| Year |
2010 |
Publication |
13th International worshop on structural and syntactic pattern recognition and 8th international worshop on statistical pattern recognition |
Abbreviated Journal |
|
| Volume |
6218 |
Issue |
|
Pages |
223–232 |
| Keywords |
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| Abstract |
Although graph embedding has recently been used to extend statistical pattern recognition techniques to the graph domain, some existing embeddings are usually computationally expensive as they rely on classical graph-based operations. In this paper we present a new way to embed graphs into vector spaces by first encapsulating the information stored in the original graph under another graph representation by clustering the attributes of the graphs to be processed. This new representation makes the association of graphs to vectors an easy step by just arranging both node attributes and the adjacency matrix in the form of vectors. To test our method, we use two different databases of graphs whose nodes attributes are of different nature. A comparison with a reference method permits to show that this new embedding is better in terms of classification rates, while being much more faster. |
| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
In E.R. Hancock, R.C. Wilson, T. Windeatt, I. Ulusoy and F. Escolano, |
| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
LNCS |
| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-642-14979-5 |
Medium |
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| Area |
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Expedition |
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Conference |
S+SSPR |
| Notes |
DAG |
Approved |
no |
| Call Number |
DAG @ dag @ GiV2010 |
Serial |
1416 |
| Permanent link to this record |
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| Author |
Carles Fernandez; Jordi Gonzalez; Xavier Roca |
| Title |
Automatic Learning of Background Semantics in Generic Surveilled Scenes |
Type |
Conference Article |
| Year |
2010 |
Publication |
11th European Conference on Computer Vision |
Abbreviated Journal |
|
| Volume |
6313 |
Issue |
II |
Pages |
678–692 |
| Keywords |
|
| Abstract |
Advanced surveillance systems for behavior recognition in outdoor traffic scenes depend strongly on the particular configuration of the scenario. Scene-independent trajectory analysis techniques statistically infer semantics in locations where motion occurs, and such inferences are typically limited to abnormality. Thus, it is interesting to design contributions that automatically categorize more specific semantic regions. State-of-the-art approaches for unsupervised scene labeling exploit trajectory data to segment areas like sources, sinks, or waiting zones. Our method, in addition, incorporates scene-independent knowledge to assign more meaningful labels like crosswalks, sidewalks, or parking spaces. First, a spatiotemporal scene model is obtained from trajectory analysis. Subsequently, a so-called GI-MRF inference process reinforces spatial coherence, and incorporates taxonomy-guided smoothness constraints. Our method achieves automatic and effective labeling of conceptual regions in urban scenarios, and is robust to tracking errors. Experimental validation on 5 surveillance databases has been conducted to assess the generality and accuracy of the segmentations. The resulting scene models are used for model-based behavior analysis. |
| Address |
Crete (Greece) |
| Corporate Author |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
LNCS |
| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-642-15551-2 |
Medium |
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| Area |
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Expedition |
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Conference |
ECCV |
| Notes |
ISE |
Approved |
no |
| Call Number |
ISE @ ise @ FGR2010 |
Serial |
1439 |
| Permanent link to this record |
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| Author |
Marco Pedersoli; Jordi Gonzalez; Andrew Bagdanov; Juan J. Villanueva |
| Title |
Recursive Coarse-to-Fine Localization for fast Object Recognition |
Type |
Conference Article |
| Year |
2010 |
Publication |
11th European Conference on Computer Vision |
Abbreviated Journal |
|
| Volume |
6313 |
Issue |
II |
Pages |
280–293 |
| Keywords |
|
| Abstract |
Cascading techniques are commonly used to speed-up the scan of an image for object detection. However, cascades of detectors are slow to train due to the high number of detectors and corresponding thresholds to learn. Furthermore, they do not use any prior knowledge about the scene structure to decide where to focus the search. To handle these problems, we propose a new way to scan an image, where we couple a recursive coarse-to-fine refinement together with spatial constraints of the object location. For doing that we split an image into a set of uniformly distributed neighborhood regions, and for each of these we apply a local greedy search over feature resolutions. The neighborhood is defined as a scanning region that only one object can occupy. Therefore the best hypothesis is obtained as the location with maximum score and no thresholds are needed. We present an implementation of our method using a pyramid of HOG features and we evaluate it on two standard databases, VOC2007 and INRIA dataset. Results show that the Recursive Coarse-to-Fine Localization (RCFL) achieves a 12x speed-up compared to standard sliding windows. Compared with a cascade of multiple resolutions approach our method has slightly better performance in speed and Average-Precision. Furthermore, in contrast to cascading approach, the speed-up is independent of image conditions, the number of detected objects and clutter. |
| Address |
Crete (Greece) |
| Corporate Author |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
LNCS |
| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-642-15566-6 |
Medium |
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| Area |
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Expedition |
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Conference |
ECCV |
| Notes |
ISE |
Approved |
no |
| Call Number |
DAG @ dag @ PGB2010 |
Serial |
1438 |
| Permanent link to this record |
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| |
| Author |
Jaume Gibert; Ernest Valveny; Horst Bunke |
| Title |
Graph of Words Embedding for Molecular Structure-Activity Relationship Analysis |
Type |
Conference Article |
| Year |
2010 |
Publication |
15th Iberoamerican Congress on Pattern Recognition |
Abbreviated Journal |
|
| Volume |
6419 |
Issue |
|
Pages |
30–37 |
| Keywords |
|
| Abstract |
Structure-Activity relationship analysis aims at discovering chemical activity of molecular compounds based on their structure. In this article we make use of a particular graph representation of molecules and propose a new graph embedding procedure to solve the problem of structure-activity relationship analysis. The embedding is essentially an arrangement of a molecule in the form of a vector by considering frequencies of appearing atoms and frequencies of covalent bonds between them. Results on two benchmark databases show the effectiveness of the proposed technique in terms of recognition accuracy while avoiding high operational costs in the transformation. |
| Address |
Sao Paulo, Brazil |
| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
LNCS |
| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-642-16686-0 |
Medium |
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| Area |
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Expedition |
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Conference |
CIARP |
| Notes |
DAG |
Approved |
no |
| Call Number |
DAG @ dag @ GVB2010 |
Serial |
1462 |
| Permanent link to this record |
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| |
| Author |
Cesar Isaza; Joaquin Salas; Bogdan Raducanu |
| Title |
Toward the Detection of Urban Infrastructures Edge Shadows |
Type |
Conference Article |
| Year |
2010 |
Publication |
12th International Conference on Advanced Concepts for Intelligent Vision Systems |
Abbreviated Journal |
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| Volume |
6474 |
Issue |
I |
Pages |
30–37 |
| Keywords |
|
| Abstract |
In this paper, we propose a novel technique to detect the shadows cast by urban infrastructure, such as buildings, billboards, and traffic signs, using a sequence of images taken from a fixed camera. In our approach, we compute two different background models in parallel: one for the edges and one for the reflected light intensity. An algorithm is proposed to train the system to distinguish between moving edges in general and edges that belong to static objects, creating an edge background model. Then, during operation, a background intensity model allow us to separate between moving and static objects. Those edges included in the moving objects and those that belong to the edge background model are subtracted from the current image edges. The remaining edges are the ones cast by urban infrastructure. Our method is tested on a typical crossroad scene and the results show that the approach is sound and promising. |
| Address |
Sydney, Australia |
| Corporate Author |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
eds. Blanc–Talon et al |
| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
LNCS |
| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-642-17687-6 |
Medium |
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| Area |
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Expedition |
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Conference |
ACIVS |
| Notes |
OR;MV |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ ISR2010 |
Serial |
1458 |
| Permanent link to this record |
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| |
| Author |
Muhammad Muzzamil Luqman; Josep Llados; Jean-Yves Ramel; Thierry Brouard |
| Title |
A Fuzzy-Interval Based Approach For Explicit Graph Embedding, Recognizing Patterns in Signals, Speech, Images and Video |
Type |
Conference Article |
| Year |
2010 |
Publication |
20th International Conference on Pattern Recognition |
Abbreviated Journal |
|
| Volume |
6388 |
Issue |
|
Pages |
93–98 |
| Keywords |
|
| Abstract |
We present a new method for explicit graph embedding. Our algorithm extracts a feature vector for an undirected attributed graph. The proposed feature vector encodes details about the number of nodes, number of edges, node degrees, the attributes of nodes and the attributes of edges in the graph. The first two features are for the number of nodes and the number of edges. These are followed by w features for node degrees, m features for k node attributes and n features for l edge attributes — which represent the distribution of node degrees, node attribute values and edge attribute values, and are obtained by defining (in an unsupervised fashion), fuzzy-intervals over the list of node degrees, node attributes and edge attributes. Experimental results are provided for sample data of ICPR2010 contest GEPR. |
| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
Springer, Heidelberg |
Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
LNCS |
| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-642-17710-1 |
Medium |
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| Area |
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Expedition |
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Conference |
ICPR |
| Notes |
DAG |
Approved |
no |
| Call Number |
DAG @ dag @ LLR2010 |
Serial |
1459 |
| Permanent link to this record |
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| |
| Author |
Sergio Escalera; David M.J. Tax; Oriol Pujol; Petia Radeva; Robert P.W. Duin |
| Title |
Multi-Class Classification in Image Analysis Via Error-Correcting Output Codes |
Type |
Book Chapter |
| Year |
2011 |
Publication |
Innovations in Intelligent Image Analysis |
Abbreviated Journal |
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| Volume |
339 |
Issue |
|
Pages |
7-29 |
| Keywords |
|
| Abstract |
A common way to model multi-class classification problems is by means of Error-Correcting Output Codes (ECOC). Given a multi-class problem, the ECOC technique designs a codeword for each class, where each position of the code identifies the membership of the class for a given binary problem.A classification decision is obtained by assigning the label of the class with the closest code. In this paper, we overview the state-of-the-art on ECOC designs and test them in real applications. Results on different multi-class data sets show the benefits of using the ensemble of classifiers when categorizing objects in images. |
| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
Berlin |
Editor |
H. Kawasnicka; L.Jain |
| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
1860-949X |
ISBN |
978-3-642-17933-4 |
Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
MILAB;HuPBA |
Approved |
no |
| Call Number |
Admin @ si @ ETP2011 |
Serial |
1746 |
| Permanent link to this record |
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| Author |
Marçal Rusiñol; David Aldavert; Dimosthenis Karatzas; Ricardo Toledo; Josep Llados |
| Title |
Interactive Trademark Image Retrieval by Fusing Semantic and Visual Content. Advances in Information Retrieval |
Type |
Conference Article |
| Year |
2011 |
Publication |
33rd European Conference on Information Retrieval |
Abbreviated Journal |
|
| Volume |
6611 |
Issue |
|
Pages |
314-325 |
| Keywords |
|
| Abstract |
In this paper we propose an efficient queried-by-example retrieval system which is able to retrieve trademark images by similarity from patent and trademark offices' digital libraries. Logo images are described by both their semantic content, by means of the Vienna codes, and their visual contents, by using shape and color as visual cues. The trademark descriptors are then indexed by a locality-sensitive hashing data structure aiming to perform approximate k-NN search in high dimensional spaces in sub-linear time. The resulting ranked lists are combined by using the Condorcet method and a relevance feedback step helps to iteratively revise the query and refine the obtained results. The experiments demonstrate the effectiveness and efficiency of this system on a realistic and large dataset. |
| Address |
Dublin, Ireland |
| Corporate Author |
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Thesis |
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| Publisher |
Springer |
Place of Publication |
Berlin |
Editor |
P. Clough; C. Foley; C. Gurrin; G.J.F. Jones; W. Kraaij; H. Lee; V. Murdoch |
| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
LNCS |
| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
|
ISBN |
978-3-642-20160-8 |
Medium |
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| Area |
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Expedition |
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Conference |
ECIR |
| Notes |
DAG; RV;ADAS |
Approved |
no |
| Call Number |
Admin @ si @ RAK2011 |
Serial |
1737 |
| Permanent link to this record |
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| |
| Author |
Maria Vanrell; Naila Murray; Robert Benavente; C. Alejandro Parraga; Xavier Otazu; Ramon Baldrich |
| Title |
Perception Based Representations for Computational Colour |
Type |
Conference Article |
| Year |
2011 |
Publication |
3rd International Workshop on Computational Color Imaging |
Abbreviated Journal |
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| Volume |
6626 |
Issue |
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Pages |
16-30 |
| Keywords |
colour perception, induction, naming, psychophysical data, saliency, segmentation |
| Abstract |
The perceived colour of a stimulus is dependent on multiple factors stemming out either from the context of the stimulus or idiosyncrasies of the observer. The complexity involved in combining these multiple effects is the main reason for the gap between classical calibrated colour spaces from colour science and colour representations used in computer vision, where colour is just one more visual cue immersed in a digital image where surfaces, shadows and illuminants interact seemingly out of control. With the aim to advance a few steps towards bridging this gap we present some results on computational representations of colour for computer vision. They have been developed by introducing perceptual considerations derived from the interaction of the colour of a point with its context. We show some techniques to represent the colour of a point influenced by assimilation and contrast effects due to the image surround and we show some results on how colour saliency can be derived in real images. We outline a model for automatic assignment of colour names to image points directly trained on psychophysical data. We show how colour segments can be perceptually grouped in the image by imposing shading coherence in the colour space. |
| Address |
Milan, Italy |
| Corporate Author |
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Thesis |
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| Publisher |
Springer-Verlag |
Place of Publication |
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Editor |
Raimondo Schettini, Shoji Tominaga, Alain Trémeau |
| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
LNCS |
| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
978-3-642-20403-6 |
Medium |
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| Area |
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Expedition |
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Conference |
CCIW |
| Notes |
CIC |
Approved |
no |
| Call Number |
Admin @ si @ VMB2011 |
Serial |
1733 |
| Permanent link to this record |
