| Records |
| Author |
David Aldavert; Ricardo Toledo; Arnau Ramisa; Ramon Lopez de Mantaras |
| Title |
Visual Registration Method For A Low Cost Robot: Computer Vision Systems |
Type |
Conference Article |
| Year |
2009 |
Publication |
7th International Conference on Computer Vision Systems |
Abbreviated Journal |
|
| Volume |
5815 |
Issue |
|
Pages |
204–214 |
| Keywords |
|
| Abstract |
An autonomous mobile robot must face the correspondence or data association problem in order to carry out tasks like place recognition or unknown environment mapping. In order to put into correspondence two maps, most methods estimate the transformation relating the maps from matches established between low level feature extracted from sensor data. However, finding explicit matches between features is a challenging and computationally expensive task. In this paper, we propose a new method to align obstacle maps without searching explicit matches between features. The maps are obtained from a stereo pair. Then, we use a vocabulary tree approach to identify putative corresponding maps followed by the Newton minimization algorithm to find the transformation that relates both maps. The proposed method is evaluated in a typical office environment showing good performance. |
| Address |
Belgica |
| 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 |
|
Series Issue |
|
Edition |
|
| ISSN |
0302-9743 |
ISBN |
978-3-642-04666-7 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
ICVS |
| Notes |
ADAS |
Approved |
no |
| Call Number |
Admin @ si @ ATR2009b |
Serial |
1247 |
| Permanent link to this record |
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| |
| Author |
Oscar Camara; Estanislao Oubel; Gemma Piella; Simone Balocco; Mathieu De Craene; Alejandro F. Frangi |
| Title |
Multi-sequence Registration of Cine, Tagged and Delay-Enhancement MRI with Shift Correction and Steerable Pyramid-Based Detagging |
Type |
Conference Article |
| Year |
2009 |
Publication |
5th International Conference on Functional Imaging and Modeling of the Heart |
Abbreviated Journal |
|
| Volume |
5528 |
Issue |
|
Pages |
330–338 |
| Keywords |
|
| Abstract |
In this work, we present a registration framework for cardiac cine MRI (cMRI), tagged (tMRI) and delay-enhancement MRI (deMRI), where the two main issues to find an accurate alignment between these images have been taking into account: the presence of tags in tMRI and respiration artifacts in all sequences. A steerable pyramid image decomposition has been used for detagging purposes since it is suitable to extract high-order oriented structures by directional adaptive filtering. Shift correction of cMRI is achieved by firstly maximizing the similarity between the Long Axis and Short Axis cMRI. Subsequently, these shift-corrected images are used as target images in a rigid registration procedure with their corresponding tMRI/deMRI in order to correct their shift. The proposed registration framework has been evaluated by 840 registration tests, considerably improving the alignment of the MR images (mean RMS error of 2.04mm vs. 5.44mm). |
| Address |
Nice, France |
| 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 |
|
Series Issue |
|
Edition |
|
| ISSN |
0302-9743 |
ISBN |
978-3-642-01931-9 |
Medium |
|
| Area |
|
Expedition |
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Conference |
FIMH |
| Notes |
MILAB |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ COP2009 |
Serial |
1255 |
| Permanent link to this record |
| |
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| |
| Author |
Bogdan Raducanu; Fadi Dornaika |
| Title |
Natural Facial Expression Recognition Using Dynamic and Static Schemes |
Type |
Conference Article |
| Year |
2009 |
Publication |
5th International Symposium on Visual Computing |
Abbreviated Journal |
|
| Volume |
5875 |
Issue |
|
Pages |
730–739 |
| Keywords |
|
| Abstract |
Affective computing is at the core of a new paradigm in HCI and AI represented by human-centered computing. Within this paradigm, it is expected that machines will be enabled with perceiving capabilities, making them aware about users’ affective state. The current paper addresses the problem of facial expression recognition from monocular videos sequences. We propose a dynamic facial expression recognition scheme, which is proven to be very efficient. Furthermore, it is conveniently compared with several static-based systems adopting different magnitude of facial expression. We provide evaluations of performance using Linear Discriminant Analysis (LDA), Non parametric Discriminant Analysis (NDA), and Support Vector Machines (SVM). We also provide performance evaluations using arbitrary test video sequences. |
| Address |
Las Vegas, USA |
| 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 |
978-3-642-10330-8 |
Medium |
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| Area |
|
Expedition |
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Conference |
ISVC |
| Notes |
OR;MV |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ RaD2009 |
Serial |
1257 |
| Permanent link to this record |
| |
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| |
| Author |
Oriol Pujol; Eloi Puertas; Carlo Gatta |
| Title |
Multi-scale Stacked Sequential Learning |
Type |
Conference Article |
| Year |
2009 |
Publication |
8th International Workshop of Multiple Classifier Systems |
Abbreviated Journal |
|
| Volume |
5519 |
Issue |
|
Pages |
262–271 |
| Keywords |
|
| Abstract |
One of the most widely used assumptions in supervised learning is that data is independent and identically distributed. This assumption does not hold true in many real cases. Sequential learning is the discipline of machine learning that deals with dependent data such that neighboring examples exhibit some kind of relationship. In the literature, there are different approaches that try to capture and exploit this correlation, by means of different methodologies. In this paper we focus on meta-learning strategies and, in particular, the stacked sequential learning approach. The main contribution of this work is two-fold: first, we generalize the stacked sequential learning. This generalization reflects the key role of neighboring interactions modeling. Second, we propose an effective and efficient way of capturing and exploiting sequential correlations that takes into account long-range interactions by means of a multi-scale pyramidal decomposition of the predicted labels. Additionally, this new method subsumes the standard stacked sequential learning approach. We tested the proposed method on two different classification tasks: text lines classification in a FAQ data set and image classification. Results on these tasks clearly show that our approach outperforms the standard stacked sequential learning. Moreover, we show that the proposed method allows to control the trade-off between the detail and the desired range of the interactions. |
| Address |
Reykjavik, Iceland |
| 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 |
|
Series Title |
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Abbreviated Series Title |
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| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
0302-9743 |
ISBN |
978-3-642-02325-5 |
Medium |
|
| Area |
|
Expedition |
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Conference |
MCS |
| Notes |
MILAB;HuPBA |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ PPG2009 |
Serial |
1260 |
| Permanent link to this record |
| |
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| |
| Author |
Santiago Segui; Laura Igual; Jordi Vitria |
| Title |
Weighted Bagging for Graph based One-Class Classifiers |
Type |
Conference Article |
| Year |
2010 |
Publication |
9th International Workshop on Multiple Classifier Systems |
Abbreviated Journal |
|
| Volume |
5997 |
Issue |
|
Pages |
1-10 |
| Keywords |
|
| Abstract |
Most conventional learning algorithms require both positive and negative training data for achieving accurate classification results. However, the problem of learning classifiers from only positive data arises in many applications where negative data are too costly, difficult to obtain, or not available at all. Minimum Spanning Tree Class Descriptor (MSTCD) was presented as a method that achieves better accuracies than other one-class classifiers in high dimensional data. However, the presence of outliers in the target class severely harms the performance of this classifier. In this paper we propose two bagging strategies for MSTCD that reduce the influence of outliers in training data. We show the improved performance on both real and artificially contaminated data. |
| Address |
Cairo, Egypt |
| Corporate Author |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
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| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
0302-9743 |
ISBN |
978-3-642-12126-5 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
MCS |
| Notes |
MILAB;OR;MV |
Approved |
no |
| Call Number |
BCNPCL @ bcnpcl @ SIV2010 |
Serial |
1284 |
| Permanent link to this record |
| |
|
| |
| 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 |
|
| 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 |
|
Editor |
A.C. Campilho and M.S. Kamel |
| Language |
|
Summary Language |
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Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
0302-9743 |
ISBN |
978-3-642-13771-6 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
ICIAR |
| Notes |
CIC |
Approved |
no |
| Call Number |
CAT @ cat @ ASV2010a |
Serial |
1325 |
| Permanent link to this record |
| |
|
| |
| 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 |
|
| Volume |
6111 |
Issue |
|
Pages |
230-239 |
| Keywords |
|
| 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 |
|
| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
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| Language |
|
Summary Language |
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Original Title |
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| Series Editor |
|
Series Title |
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Abbreviated Series Title |
LNCS |
| Series Volume |
|
Series Issue |
|
Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-642-13771-6 |
Medium |
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| Area |
|
Expedition |
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Conference |
ICIAR |
| Notes |
ADAS |
Approved |
no |
| Call Number |
ADAS @ adas @ OnS2010 |
Serial |
1342 |
| Permanent link to this record |
| |
|
| |
| 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 |
|
| 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 |
|
| 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 |
|
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 |
|
Edition |
|
| ISSN |
0302-9743 |
ISBN |
978-3-642-14979-5 |
Medium |
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| Area |
|
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 |
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 |
|
Summary Language |
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Original Title |
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| Series Editor |
|
Series Title |
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Abbreviated Series Title |
LNCS |
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
0302-9743 |
ISBN |
978-3-642-15566-6 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
ECCV |
| Notes |
ISE |
Approved |
no |
| Call Number |
DAG @ dag @ PGB2010 |
Serial |
1438 |
| 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 |
|
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 |
|
Series Issue |
|
Edition |
|
| ISSN |
0302-9743 |
ISBN |
978-3-642-15551-2 |
Medium |
|
| 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 |
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 |
|
| 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 |
|
Summary Language |
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Original Title |
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| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
0302-9743 |
ISBN |
978-3-642-17687-6 |
Medium |
|
| Area |
|
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 |
Debora Gil; Aura Hernandez-Sabate; Mireia Burnat; Steven Jansen; Jordi Martinez-Vilalta |
| Title |
Structure-Preserving Smoothing of Biomedical Images |
Type |
Conference Article |
| Year |
2009 |
Publication |
13th International Conference on Computer Analysis of Images and Patterns |
Abbreviated Journal |
|
| Volume |
5702 |
Issue |
|
Pages |
427-434 |
| Keywords |
non-linear smoothing; differential geometry; anatomical structures segmentation; cardiac magnetic resonance; computerized tomography. |
| Abstract |
Smoothing of biomedical images should preserve gray-level transitions between adjacent tissues, while restoring contours consistent with anatomical structures. Anisotropic diffusion operators are based on image appearance discontinuities (either local or contextual) and might fail at weak inter-tissue transitions. Meanwhile, the output of block-wise and morphological operations is prone to present a block structure due to the shape and size of the considered pixel neighborhood. In this contribution, we use differential geometry concepts to define a diffusion operator that restricts to image consistent level-sets. In this manner, the final state is a non-uniform intensity image presenting homogeneous inter-tissue transitions along anatomical structures, while smoothing intra-structure texture. Experiments on different types of medical images (magnetic resonance, computerized tomography) illustrate its benefit on a further process (such as segmentation) of images. |
| Address |
Münster, Germany |
| 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 |
|
Abbreviated Series Title |
LNCS |
| Series Volume |
|
Series Issue |
|
Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-642-03766-5 |
Medium |
|
| Area |
|
Expedition |
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Conference |
CAIP |
| Notes |
IAM |
Approved |
no |
| Call Number |
IAM @ iam @ GHB2009 |
Serial |
1527 |
| Permanent link to this record |
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| |
| Author |
Naveen Onkarappa; Angel Sappa |
| Title |
Space Variant Representations for Mobile Platform Vision Applications |
Type |
Conference Article |
| Year |
2011 |
Publication |
14th International Conference on Computer Analysis of Images and Patterns |
Abbreviated Journal |
|
| Volume |
6855 |
Issue |
II |
Pages |
146-154 |
| Keywords |
|
| Abstract |
The log-polar space variant representation, motivated by biological vision, has been widely studied in the literature. Its data reduction and invariance properties made it useful in many vision applications. However, due to its nature, it fails in preserving features in the periphery. In the current work, as an attempt to overcome this problem, we propose a novel space-variant representation. It is evaluated and proved to be better than the log-polar representation in preserving the peripheral information, crucial for on-board mobile vision applications. The evaluation is performed by comparing log-polar and the proposed representation once they are used for estimating dense optical flow. |
| Address |
Seville, Spain |
| Corporate Author |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
P. Real, D. Diaz, H. Molina, A. Berciano, W. Kropatsch |
| 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 |
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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 |
978-3-642-23677-8 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
CAIP |
| Notes |
ADAS |
Approved |
no |
| Call Number |
NaS2011; ADAS @ adas @ |
Serial |
1686 |
| Permanent link to this record |
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| |
| Author |
Lluis Pere de las Heras; Ahmed Sheraz; Marcus Liwicki; Ernest Valveny; Gemma Sanchez |
| Title |
Statistical Segmentation and Structural Recognition for Floor Plan Interpretation |
Type |
Journal Article |
| Year |
2014 |
Publication |
International Journal on Document Analysis and Recognition |
Abbreviated Journal |
IJDAR |
| Volume |
17 |
Issue |
3 |
Pages |
221-237 |
| Keywords |
|
| Abstract |
A generic method for floor plan analysis and interpretation is presented in this article. The method, which is mainly inspired by the way engineers draw and interpret floor plans, applies two recognition steps in a bottom-up manner. First, basic building blocks, i.e., walls, doors, and windows are detected using a statistical patch-based segmentation approach. Second, a graph is generated, and structural pattern recognition techniques are applied to further locate the main entities, i.e., rooms of the building. The proposed approach is able to analyze any type of floor plan regardless of the notation used. We have evaluated our method on different publicly available datasets of real architectural floor plans with different notations. The overall detection and recognition accuracy is about 95 %, which is significantly better than any other state-of-the-art method. Our approach is generic enough such that it could be easily adopted to the recognition and interpretation of any other printed machine-generated structured documents. |
| 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 |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
1433-2833 |
ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
DAG; ADAS; 600.076; 600.077 |
Approved |
no |
| Call Number |
HSL2014 |
Serial |
2370 |
| Permanent link to this record |
| |
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| |
| Author |
Mario Rojas; David Masip; Jordi Vitria |
| Title |
Automatic Detection of Facial Feature Points via HOGs and Geometric Prior Models |
Type |
Conference Article |
| Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
|
| Volume |
6669 |
Issue |
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Pages |
371-378 |
| Keywords |
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| Abstract |
Most applications dealing with problems involving the face require a robust estimation of the facial salient points. Nevertheless, this estimation is not usually an automated preprocessing step in applications dealing with facial expression recognition. In this paper we present a simple method to detect facial salient points in the face. It is based on a prior Point Distribution Model and a robust object descriptor. The model learns the distribution of the points from the training data, as well as the amount of variation in location each point exhibits. Using this model, we reduce the search areas to look for each point. In addition, we also exploit the global consistency of the points constellation, increasing the detection accuracy. The method was tested on two separate data sets and the results, in some cases, outperform the state of the art. |
| Address |
Las Palmas de Gran Canaria. Spain |
| 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 |
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| Series Volume |
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Series Issue |
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Edition |
|
| ISSN |
0302-9743 |
ISBN |
978-3-642-21256-7 |
Medium |
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| Area |
|
Expedition |
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Conference |
IbPRIA |
| Notes |
OR;MV |
Approved |
no |
| Call Number |
Admin @ si @ RMV2011a |
Serial |
1731 |
| Permanent link to this record |
