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Author |
Ariel Amato |
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Title |
Environment-Independent Moving Cast Shadow Suppression in Video Surveillance |
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Book Whole |
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Year |
2012 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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This thesis is devoted to moving shadows detection and suppression. Shadows could be defined as the parts of the scene that are not directly illuminated by a light source due to obstructing object or objects. Often, moving shadows in images sequences are undesirable since they could cause degradation of the expected results during processing of images for object detection, segmentation, scene surveillance or similar purposes. In this thesis first moving shadow detection methods are exhaustively overviewed. Beside the mentioned methods from literature and to compensate their limitations a new moving shadow detection method is proposed. It requires no prior knowledge about the scene, nor is it restricted to assumptions about specific scene structures. Furthermore, the technique can detect both achromatic and chromatic shadows even in the presence of camouflage that occurs when foreground regions are very similar in color to shadowed regions. The method exploits local color constancy properties due to reflectance suppression over shadowed regions. To detect shadowed regions in a scene the values of the background image are divided by values of the current frame in the RGB color space. In the thesis how this luminance ratio can be used to identify segments with low gradient constancy is shown, which in turn distinguish shadows from foreground. Experimental results on a collection of publicly available datasets illustrate the superior performance of the proposed method compared with the most sophisticated state-of-the-art shadow detection algorithms. These results show that the proposed approach is robust and accurate over a broad range of shadow types and challenging video conditions. |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Mikhail Mozerov;Jordi Gonzalez |
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ISE |
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no |
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Call Number |
Admin @ si @ Ama2012 |
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2201 |
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Author |
Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera |
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Title |
Efficient pairwise classification using Local Cross Off strategy |
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Conference Article |
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Year |
2012 |
Publication |
25th Canadian Conference on Artificial Intelligence |
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Volume |
7310 |
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Pages |
25-36 |
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The pairwise classification approach tends to perform better than other well-known approaches when dealing with multiclass classification problems. In the pairwise approach, however, the nuisance votes of many irrelevant classifiers may result in a wrong prediction class. To overcome this problem, a novel method, Local Crossing Off (LCO), is presented and evaluated in this paper. The proposed LCO system takes advantage of nearest neighbor classification algorithm because of its simplicity and speed, as well as the strength of other two powerful binary classifiers to discriminate between two classes. This paper provides a set of experimental results on 20 datasets using two base learners: Neural Networks and Support Vector Machines. The results show that the proposed technique not only achieves better classification accuracy, but also is computationally more efficient for tackling classification problems which have a relatively large number of target classes. |
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Toronto, Ontario |
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LNCS |
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0302-9743 |
ISBN |
978-3-642-30352-4 |
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AI |
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Notes |
HuPBA;MILAB |
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no |
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Call Number |
Admin @ si @ BGE2012c |
Serial |
2044 |
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Author |
Jon Almazan; Albert Gordo; Alicia Fornes; Ernest Valveny |
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Title |
Efficient Exemplar Word Spotting |
Type |
Conference Article |
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Year |
2012 |
Publication |
23rd British Machine Vision Conference |
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67.1- 67.11 |
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In this paper we propose an unsupervised segmentation-free method for word spotting in document images.
Documents are represented with a grid of HOG descriptors, and a sliding window approach is used to locate the document regions that are most similar to the query. We use the exemplar SVM framework to produce a better representation of the query in an unsupervised way. Finally, the document descriptors are precomputed and compressed with Product Quantization. This offers two advantages: first, a large number of documents can be kept in RAM memory at the same time. Second, the sliding window becomes significantly faster since distances between quantized HOG descriptors can be precomputed. Our results significantly outperform other segmentation-free methods in the literature, both in accuracy and in speed and memory usage. |
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1-901725-46-4 |
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BMVC |
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DAG |
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no |
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DAG @ dag @ AGF2012 |
Serial |
1984 |
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Author |
Adriana Romero; Simeon Petkov; Carlo Gatta; M.Sabate; Petia Radeva |
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Title |
Efficient automatic segmentation of vessels |
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Conference Article |
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Year |
2012 |
Publication |
16th Conference on Medical Image Understanding and Analysis |
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Swansea, United Kingdom |
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MIUA |
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MILAB |
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no |
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Call Number |
Admin @ si @ |
Serial |
2137 |
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Author |
Josep M. Gonfaus; Theo Gevers; Arjan Gijsenij; Xavier Roca; Jordi Gonzalez |
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Title |
Edge Classification using Photo-Geo metric features |
Type |
Conference Article |
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Year |
2012 |
Publication |
21st International Conference on Pattern Recognition |
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Pages |
1497 - 1500 |
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Edges are caused by several imaging cues such as shadow, material and illumination transitions. Classification methods have been proposed which are solely based on photometric information, ignoring geometry to classify the physical nature of edges in images. In this paper, the aim is to present a novel strategy to handle both photometric and geometric information for edge classification. Photometric information is obtained through the use of quasi-invariants while geometric information is derived from the orientation and contrast of edges. Different combination frameworks are compared with a new principled approach that captures both information into the same descriptor. From large scale experiments on different datasets, it is shown that, in addition to photometric information, the geometry of edges is an important visual cue to distinguish between different edge types. It is concluded that by combining both cues the performance improves by more than 7% for shadows and highlights. |
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ISSN |
1051-4651 |
ISBN |
978-1-4673-2216-4 |
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ICPR |
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Notes |
ISE |
Approved |
no |
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Call Number |
Admin @ si @ GGG2012b |
Serial |
2142 |
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Author |
Francisco Cruz; Oriol Ramos Terrades |
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Title |
Document segmentation using relative location features |
Type |
Conference Article |
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Year |
2012 |
Publication |
21st International Conference on Pattern Recognition |
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Pages |
1562-1565 |
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In this paper we evaluate the use of Relative Location Features (RLF) on a historical document segmentation task, and compare the quality of the results obtained on structured and unstructured documents using RLF and not using them. We prove that using these features improve the final segmentation on documents with a strong structure, while their application on unstructured documents does not show significant improvement. Although this paper is not focused on segmenting unstructured documents, results obtained on a benchmark dataset are equal or even overcome previous results of similar works. |
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Tsukuba Science City, Japan |
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ICPR |
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Notes |
DAG |
Approved |
no |
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Call Number |
Admin @ si @ CrR2012 |
Serial |
2051 |
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Author |
Albert Gordo; Florent Perronnin; Ernest Valveny |
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Title |
Document classification using multiple views |
Type |
Conference Article |
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Year |
2012 |
Publication |
10th IAPR International Workshop on Document Analysis Systems |
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Pages |
33-37 |
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The combination of multiple features or views when representing documents or other kinds of objects usually leads to improved results in classification (and retrieval) tasks. Most systems assume that those views will be available both at training and test time. However, some views may be too `expensive' to be available at test time. In this paper, we consider the use of Canonical Correlation Analysis to leverage `expensive' views that are available only at training time. Experimental results show that this information may significantly improve the results in a classification task. |
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Australia |
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IEEE Computer Society Washington |
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978-0-7695-4661-2 |
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DAS |
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DAG |
Approved |
no |
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Call Number |
Admin @ si @ GPV2012 |
Serial |
2049 |
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Author |
Noha Elfiky; Fahad Shahbaz Khan; Joost Van de Weijer; Jordi Gonzalez |
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Title |
Discriminative Compact Pyramids for Object and Scene Recognition |
Type |
Journal Article |
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Year |
2012 |
Publication |
Pattern Recognition |
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PR |
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Volume |
45 |
Issue |
4 |
Pages |
1627-1636 |
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Abstract |
Spatial pyramids have been successfully applied to incorporating spatial information into bag-of-words based image representation. However, a major drawback is that it leads to high dimensional image representations. In this paper, we present a novel framework for obtaining compact pyramid representation. First, we investigate the usage of the divisive information theoretic feature clustering (DITC) algorithm in creating a compact pyramid representation. In many cases this method allows us to reduce the size of a high dimensional pyramid representation up to an order of magnitude with little or no loss in accuracy. Furthermore, comparison to clustering based on agglomerative information bottleneck (AIB) shows that our method obtains superior results at significantly lower computational costs. Moreover, we investigate the optimal combination of multiple features in the context of our compact pyramid representation. Finally, experiments show that the method can obtain state-of-the-art results on several challenging data sets. |
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0031-3203 |
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Notes |
ISE; CAT;CIC |
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no |
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Call Number |
Admin @ si @ EKW2012 |
Serial |
1807 |
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Author |
Ricard Borras; Agata Lapedriza; Laura Igual |
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Title |
Depth Information in Human Gait Analysis: An Experimental Study on Gender Recognition |
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Conference Article |
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Year |
2012 |
Publication |
9th International Conference on Image Analysis and Recognition |
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Volume |
7325 |
Issue |
II |
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98-105 |
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This work presents DGait, a new gait database acquired with a depth camera. This database contains videos from 53 subjects walking in different directions. The intent of this database is to provide a public set to explore whether the depth can be used as an additional information source for gait classification purposes. Each video is labelled according to subject, gender and age. Furthermore, for each subject and view point, we provide initial and final frames of an entire walk cycle. On the other hand, we perform gait-based gender classification experiments with DGait database, in order to illustrate the usefulness of depth information for this purpose. In our experiments, we extract 2D and 3D gait features based on shape descriptors, and compare the performance of these features for gender identification, using a Kernel SVM. The obtained results show that depth can be an information source of great relevance for gait classification problems. |
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Aveiro, Portugal |
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Springer Berlin Heidelberg |
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0302-9743 |
ISBN |
978-3-642-31297-7 |
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ICIAR |
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Notes |
OR; MILAB;MV |
Approved |
no |
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Call Number |
Admin @ si @ BLI2012 |
Serial |
2009 |
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Author |
Marçal Rusiñol; Lluis Pere de las Heras; Joan Mas; Oriol Ramos Terrades; Dimosthenis Karatzas; Anjan Dutta; Gemma Sanchez; Josep Llados |
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Title |
CVC-UAB's participation in the Flowchart Recognition Task of CLEF-IP 2012 |
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Conference Article |
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Year |
2012 |
Publication |
Conference and Labs of the Evaluation Forum |
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Roma |
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CLEF |
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DAG |
Approved |
no |
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Call Number |
Admin @ si @ RHM2012 |
Serial |
2072 |
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Author |
Alicia Fornes; Anjan Dutta; Albert Gordo; Josep Llados |
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Title |
CVC-MUSCIMA: A Ground-Truth of Handwritten Music Score Images for Writer Identification and Staff Removal |
Type |
Journal Article |
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Year |
2012 |
Publication |
International Journal on Document Analysis and Recognition |
Abbreviated Journal |
IJDAR |
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15 |
Issue |
3 |
Pages |
243-251 |
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Keywords |
Music scores; Handwritten documents; Writer identification; Staff removal; Performance evaluation; Graphics recognition; Ground truths |
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Abstract |
0,405JCR
The analysis of music scores has been an active research field in the last decades. However, there are no publicly available databases of handwritten music scores for the research community. In this paper we present the CVC-MUSCIMA database and ground-truth of handwritten music score images. The dataset consists of 1,000 music sheets written by 50 different musicians. It has been especially designed for writer identification and staff removal tasks. In addition to the description of the dataset, ground-truth, partitioning and evaluation metrics, we also provide some base-line results for easing the comparison between different approaches. |
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1433-2833 |
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DAG |
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no |
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Admin @ si @ FDG2012 |
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2129 |
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Author |
Pedro Martins; Paulo Carvalho; Carlo Gatta |
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Title |
Context Aware Keypoint Extraction for Robust Image Representation |
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Conference Article |
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Year |
2012 |
Publication |
23rd British Machine Vision Conference |
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100.1 - 100.12 |
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BMVC |
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MILAB |
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no |
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Call Number |
Admin @ si @ MCG2012a |
Serial |
2140 |
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Author |
Jordi Roca |
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Title |
Constancy and inconstancy in categorical colour perception |
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Book Whole |
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2012 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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To recognise objects is perhaps the most important task an autonomous system, either biological or artificial needs to perform. In the context of human vision, this is partly achieved by recognizing the colour of surfaces despite changes in the wavelength distribution of the illumination, a property called colour constancy. Correct surface colour recognition may be adequately accomplished by colour category matching without the need to match colours precisely, therefore categorical colour constancy is likely to play an important role for object identification to be successful. The main aim of this work is to study the relationship between colour constancy and categorical colour perception. Previous studies of colour constancy have shown the influence of factors such the spatio-chromatic properties of the background, individual observer's performance, semantics, etc. However there is very little systematic study of these influences. To this end, we developed a new approach to colour constancy which includes both individual observers' categorical perception, the categorical structure of the background, and their interrelations resulting in a more comprehensive characterization of the phenomenon. In our study, we first developed a new method to analyse the categorical structure of 3D colour space, which allowed us to characterize individual categorical colour perception as well as quantify inter-individual variations in terms of shape and centroid location of 3D categorical regions. Second, we developed a new colour constancy paradigm, termed chromatic setting, which allows measuring the precise location of nine categorically-relevant points in colour space under immersive illumination. Additionally, we derived from these measurements a new colour constancy index which takes into account the magnitude and orientation of the chromatic shift, memory effects and the interrelations among colours and a model of colour naming tuned to each observer/adaptation state. Our results lead to the following conclusions: (1) There exists large inter-individual variations in the categorical structure of colour space, and thus colour naming ability varies significantly but this is not well predicted by low-level chromatic discrimination ability; (2) Analysis of the average colour naming space suggested the need for an additional three basic colour terms (turquoise, lilac and lime) for optimal colour communication; (3) Chromatic setting improved the precision of more complex linear colour constancy models and suggested that mechanisms other than cone gain might be best suited to explain colour constancy; (4) The categorical structure of colour space is broadly stable under illuminant changes for categorically balanced backgrounds; (5) Categorical inconstancy exists for categorically unbalanced backgrounds thus indicating that categorical information perceived in the initial stages of adaptation may constrain further categorical perception. |
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Ph.D. thesis |
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Maria Vanrell;C. Alejandro Parraga |
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CIC |
Approved |
no |
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Call Number |
Admin @ si @ Roc2012 |
Serial |
2893 |
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Permanent link to this record |
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Author |
Angel Sappa; George A. Triantafyllid |
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Title |
Computer Graphics and Imaging |
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Book Whole |
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2012 |
Publication |
Computer Graphics and Imaging |
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Crete, Greece |
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978-0-88986-921-9 |
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no |
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Admin @ si @ Sap2012 |
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2067 |
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Author |
Sergio Vera; Debora Gil; Agnes Borras; F. Javier Sanchez; Frederic Perez; Marius G. Linguraru; Miguel Angel Gonzalez Ballester |
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Title |
Computation and Evaluation of Medial Surfaces for Shape Representation of Abdominal Organs |
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Book Chapter |
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2012 |
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Workshop on Computational and Clinical Applications in Abdominal Imaging |
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7029 |
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223–230 |
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medial manifolds, abdomen. |
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Abstract |
Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Existing methods show excellent results when applied to 2D
objects, but their quality drops across dimensions. This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial
manifolds that avoid degenerated medial axis segments; second, we introduce an energy based method which performs independently of the dimension. We evaluate quantitatively the performance of our
method with respect to existing approaches, by applying them to synthetic shapes of known medial geometry. Finally, we show results on shape representation of multiple abdominal organs,
exploring the use of medial manifolds for the representation of multi-organ relations. |
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Toronto; Canada; |
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Springer Link |
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Berlin |
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H. Yoshida et al |
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English |
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English |
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Lecture Notes in Computer Science |
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0302-9743 |
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978-3-642-28556-1 |
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ABDI |
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IAM;MV |
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no |
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Call Number |
IAM @ iam @ VGB2012 |
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1834 |
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