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Author |
Bogdan Raducanu; Jordi Vitria; D. Gatica-Perez |
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Title |
You are Fired! Nonverbal Role Analysis in Competitive Meetings |
Type |
Conference Article |
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Year |
2009 |
Publication |
IEEE International Conference on Audio, Speech and Signal Processing |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
1949–1952 |
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Keywords |
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Abstract |
This paper addresses the problem of social interaction analysis in competitive meetings, using nonverbal cues. For our study, we made use of ldquoThe Apprenticerdquo reality TV show, which features a competition for a real, highly paid corporate job. Our analysis is centered around two tasks regarding a person's role in a meeting: predicting the person with the highest status and predicting the fired candidates. The current study was carried out using nonverbal audio cues. Results obtained from the analysis of a full season of the show, representing around 90 minutes of audio data, are very promising (up to 85.7% of accuracy in the first case and up to 92.8% in the second case). Our approach is based only on the nonverbal interaction dynamics during the meeting without relying on the spoken words. |
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Address |
Taipei, Taiwan |
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Edition |
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ISSN |
1520-6149 |
ISBN |
978-1-4244-2353-8 |
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Expedition |
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Conference |
ICASSP |
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Notes |
OR;MV |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ RVG2009 |
Serial |
1154 |
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Permanent link to this record |
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Author |
Jose Manuel Alvarez; Ferran Diego; Joan Serrat; Antonio Lopez |
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Title |
Automatic Ground-truthing using video registration for on-board detection algorithms |
Type |
Conference Article |
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Year |
2009 |
Publication |
16th IEEE International Conference on Image Processing |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
4389 - 4392 |
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Keywords |
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Abstract |
Ground-truth data is essential for the objective evaluation of object detection methods in computer vision. Many works claim their method is robust but they support it with experiments which are not quantitatively assessed with regard some ground-truth. This is one of the main obstacles to properly evaluate and compare such methods. One of the main reasons is that creating an extensive and representative ground-truth is very time consuming, specially in the case of video sequences, where thousands of frames have to be labelled. Could such a ground-truth be generated, at least in part, automatically? Though it may seem a contradictory question, we show that this is possible for the case of video sequences recorded from a moving camera. The key idea is transferring existing frame segmentations from a reference sequence into another video sequence recorded at a different time on the same track, possibly under a different ambient lighting. We have carried out experiments on several video sequence pairs and quantitatively assessed the precision of the transformed ground-truth, which prove that our approach is not only feasible but also quite accurate. |
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Address |
Cairo, Egypt |
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Series Editor |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
1522-4880 |
ISBN |
978-1-4244-5653-6 |
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Expedition |
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Conference |
ICIP |
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Notes |
ADAS |
Approved |
no |
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Call Number |
ADAS @ adas @ ADS2009 |
Serial |
1201 |
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Permanent link to this record |
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Author |
Angel Sappa; Mohammad Rouhani |
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Title |
Efficient Distance Estimation for Fitting Implicit Quadric Surfaces |
Type |
Conference Article |
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Year |
2009 |
Publication |
16th IEEE International Conference on Image Processing |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
3521–3524 |
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Keywords |
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Abstract |
This paper presents a novel approach for estimating the shortest Euclidean distance from a given point to the corresponding implicit quadric fitting surface. It first estimates the orthogonal orientation to the surface from the given point; then the shortest distance is directly estimated by intersecting the implicit surface with a line passing through the given point according to the estimated orthogonal orientation. The proposed orthogonal distance estimation is easily obtained without increasing computational complexity; hence it can be used in error minimization surface fitting frameworks. Comparisons of the proposed metric with previous approaches are provided to show both improvements in CPU time as well as in the accuracy of the obtained results. Surfaces fitted by using the proposed geometric distance estimation and state of the art metrics are presented to show the viability of the proposed approach. |
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Address |
Cairo, Egypt |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
1522-4880 |
ISBN |
978-1-4244-5653-6 |
Medium |
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Area |
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Expedition |
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Conference |
ICIP |
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Notes |
ADAS |
Approved |
no |
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Call Number |
ADAS @ adas @ SaR2009 |
Serial |
1232 |
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Permanent link to this record |
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Author |
Carlo Gatta; Petia Radeva |
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Title |
Bilateral Enhancers |
Type |
Conference Article |
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Year |
2009 |
Publication |
16th IEEE International Conference on Image Processing |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
3161-3165 |
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Abstract |
Ten years ago the concept of bilateral filtering (BF) became popular in the image processing community. The core of the idea is to blend the effect of a spatial filter, as e.g. the Gaussian filter, with the effect of a filter that acts on image values. The two filters acts on orthogonal domains of a picture: the 2D lattice of the image support and the intensity (or color) domain. The BF approach is an intuitive way to blend these two filters giving rise to algorithms that perform difficult tasks requiring a relatively simple design. In this paper we extend the concept of BF, proposing the bilateral enhancers (BE). We show how to design proper functions to obtain an edge-preserving smoothing and a selective sharpening. Moreover, we show that the proposed algorithm can perform edge-preserving smoothing and selective sharpening simultaneously in a single filtering. |
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Address |
Cairo, Egypt |
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Series Editor |
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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 |
1522-4880 |
ISBN |
978-1-4244-5653-6 |
Medium |
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Area |
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Expedition |
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Conference |
ICIP |
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Notes |
MILAB |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ GaR2009b |
Serial |
1243 |
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Permanent link to this record |
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Author |
Xavier Baro; Sergio Escalera; Jordi Vitria; Oriol Pujol; Petia Radeva |
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Title |
Traffic Sign Recognition Using Evolutionary Adaboost Detection and Forest-ECOC Classification |
Type |
Journal Article |
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Year |
2009 |
Publication |
IEEE Transactions on Intelligent Transportation Systems |
Abbreviated Journal |
TITS |
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Volume |
10 |
Issue |
1 |
Pages |
113–126 |
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Keywords |
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Abstract |
The high variability of sign appearance in uncontrolled environments has made the detection and classification of road signs a challenging problem in computer vision. In this paper, we introduce a novel approach for the detection and classification of traffic signs. Detection is based on a boosted detectors cascade, trained with a novel evolutionary version of Adaboost, which allows the use of large feature spaces. Classification is defined as a multiclass categorization problem. A battery of classifiers is trained to split classes in an Error-Correcting Output Code (ECOC) framework. We propose an ECOC design through a forest of optimal tree structures that are embedded in the ECOC matrix. The novel system offers high performance and better accuracy than the state-of-the-art strategies and is potentially better in terms of noise, affine deformation, partial occlusions, and reduced illumination. |
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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 |
1524-9050 |
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 |
OR;MILAB;HuPBA;MV |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ BEV2008 |
Serial |
1116 |
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Permanent link to this record |
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Author |
S. Chanda; Umapada Pal; Oriol Ramos Terrades |
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Title |
Word-Wise Thai and Roman Script Identification |
Type |
Journal |
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Year |
2009 |
Publication |
ACM Transactions on Asian Language Information Processing |
Abbreviated Journal |
TALIP |
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Volume |
8 |
Issue |
3 |
Pages |
1-21 |
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Keywords |
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Abstract |
In some Thai documents, a single text line of a printed document page may contain words of both Thai and Roman scripts. For the Optical Character Recognition (OCR) of such a document page it is better to identify, at first, Thai and Roman script portions and then to use individual OCR systems of the respective scripts on these identified portions. In this article, an SVM-based method is proposed for identification of word-wise printed Roman and Thai scripts from a single line of a document page. Here, at first, the document is segmented into lines and then lines are segmented into character groups (words). In the proposed scheme, we identify the script of a character group combining different character features obtained from structural shape, profile behavior, component overlapping information, topological properties, and water reservoir concept, etc. Based on the experiment on 10,000 data (words) we obtained 99.62% script identification accuracy from the proposed scheme. |
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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 |
1530-0226 |
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 |
Approved |
no |
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Call Number |
Admin @ si @ CPR2009f |
Serial |
1869 |
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Permanent link to this record |
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Author |
Fahad Shahbaz Khan; Joost Van de Weijer; Maria Vanrell |
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Title |
Top-Down Color Attention for Object Recognition |
Type |
Conference Article |
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Year |
2009 |
Publication |
12th International Conference on Computer Vision |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
979 - 986 |
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Keywords |
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Abstract |
Generally the bag-of-words based image representation follows a bottom-up paradigm. The subsequent stages of the process: feature detection, feature description, vocabulary construction and image representation are performed independent of the intentioned object classes to be detected. In such a framework, combining multiple cues such as shape and color often provides below-expected results. This paper presents a novel method for recognizing object categories when using multiple cues by separating the shape and color cue. Color is used to guide attention by means of a top-down category-specific attention map. The color attention map is then further deployed to modulate the shape features by taking more features from regions within an image that are likely to contain an object instance. This procedure leads to a category-specific image histogram representation for each category. Furthermore, we argue that the method combines the advantages of both early and late fusion. We compare our approach with existing methods that combine color and shape cues on three data sets containing varied importance of both cues, namely, Soccer ( color predominance), Flower (color and shape parity), and PASCAL VOC Challenge 2007 (shape predominance). The experiments clearly demonstrate that in all three data sets our proposed framework significantly outperforms the state-of-the-art methods for combining color and shape information. |
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Address |
Kyoto, Japan |
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Corporate Author |
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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 |
1550-5499 |
ISBN |
978-1-4244-4420-5 |
Medium |
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Area |
|
Expedition |
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Conference |
ICCV |
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Notes |
CIC |
Approved |
no |
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|
Call Number |
CAT @ cat @ SWV2009 |
Serial |
1196 |
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Permanent link to this record |
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Author |
Ivan Huerta; Michael Holte; Thomas B. Moeslund; Jordi Gonzalez |
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Title |
Detection and Removal of Chromatic Moving Shadows in Surveillance Scenarios |
Type |
Conference Article |
|
Year |
2009 |
Publication |
12th International Conference on Computer Vision |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
1499 - 1506 |
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Keywords |
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Abstract |
Segmentation in the surveillance domain has to deal with shadows to avoid distortions when detecting moving objects. Most segmentation approaches dealing with shadow detection are typically restricted to penumbra shadows. Therefore, such techniques cannot cope well with umbra shadows. Consequently, umbra shadows are usually detected as part of moving objects. In this paper we present a novel technique based on gradient and colour models for separating chromatic moving cast shadows from detected moving objects. Firstly, both a chromatic invariant colour cone model and an invariant gradient model are built to perform automatic segmentation while detecting potential shadows. In a second step, regions corresponding to potential shadows are grouped by considering “a bluish effect” and an edge partitioning. Lastly, (i) temporal similarities between textures and (ii) spatial similarities between chrominance angle and brightness distortions are analysed for all potential shadow regions in order to finally identify umbra shadows. Unlike other approaches, our method does not make any a-priori assumptions about camera location, surface geometries, surface textures, shapes and types of shadows, objects, and background. Experimental results show the performance and accuracy of our approach in different shadowed materials and illumination conditions. |
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Address |
Kyoto, Japan |
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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 |
1550-5499 |
ISBN |
978-1-4244-4420-5 |
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Area |
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Expedition |
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Conference |
ICCV |
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Notes |
|
Approved |
no |
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Call Number |
ISE @ ise @ HHM2009 |
Serial |
1213 |
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Permanent link to this record |
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Author |
Fadi Dornaika; Bogdan Raducanu |
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Title |
Simultaneous 3D face pose and person-specific shape estimation from a single image using a holistic approach |
Type |
Conference Article |
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Year |
2009 |
Publication |
IEEE Workshop on Applications of Computer Vision |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
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Keywords |
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Abstract |
This paper presents a new approach for the simultaneous estimation of the 3D pose and specific shape of a previously unseen face from a single image. The face pose is not limited to a frontal view. We describe a holistic approach based on a deformable 3D model and a learned statistical facial texture model. Rather than obtaining a person-specific facial surface, the goal of this work is to compute person-specific 3D face shape in terms of a few control parameters that are used by many applications. The proposed holistic approach estimates the 3D pose parameters as well as the face shape control parameters by registering the warped texture to a statistical face texture, which is carried out by a stochastic and genetic optimizer. The proposed approach has several features that make it very attractive: (i) it uses a single grey-scale image, (ii) it is person-independent, (iii) it is featureless (no facial feature extraction is required), and (iv) its learning stage is easy. The proposed approach lends itself nicely to 3D face tracking and face gesture recognition in monocular videos. We describe extensive experiments that show the feasibility and robustness of the proposed approach. |
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Address |
Utah, USA |
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Edition |
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ISSN |
1550-5790 |
ISBN |
978-1-4244-5497-6 |
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Expedition |
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Conference |
WACV |
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Notes |
OR;MV |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ DoR2009b |
Serial |
1256 |
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Permanent link to this record |
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Author |
Sergio Escalera; Oriol Pujol; J. Mauri; Petia Radeva |
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Title |
Intravascular Ultrasound Tissue Characterization with Sub-class Error-Correcting Output Codes |
Type |
Journal Article |
|
Year |
2009 |
Publication |
Journal of Signal Processing Systems |
Abbreviated Journal |
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Volume |
55 |
Issue |
1-3 |
Pages |
35–47 |
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Keywords |
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Abstract |
Intravascular ultrasound (IVUS) represents a powerful imaging technique to explore coronary vessels and to study their morphology and histologic properties. In this paper, we characterize different tissues based on radial frequency, texture-based, and combined features. To deal with the classification of multiple tissues, we require the use of robust multi-class learning techniques. In this sense, error-correcting output codes (ECOC) show to robustly combine binary classifiers to solve multi-class problems. In this context, we propose a strategy to model multi-class classification tasks using sub-classes information in the ECOC framework. The new strategy splits the classes into different sub-sets according to the applied base classifier. Complex IVUS data sets containing overlapping data are learnt by splitting the original set of classes into sub-classes, and embedding the binary problems in a problem-dependent ECOC design. The method automatically characterizes different tissues, showing performance improvements over the state-of-the-art ECOC techniques for different base classifiers. Furthermore, the combination of RF and texture-based features also shows improvements over the state-of-the-art approaches. |
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Series Editor |
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ISSN |
1939-8018 |
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Notes |
MILAB;HuPBA |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ EPM2009 |
Serial |
1258 |
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Permanent link to this record |
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Author |
D. Jayagopi; Bogdan Raducanu; D. Gatica-Perez |
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Title |
Characterizing conversational group dynamics using nonverbal behaviour |
Type |
Conference Article |
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Year |
2009 |
Publication |
10th IEEE International Conference on Multimedia and Expo |
Abbreviated Journal |
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Volume |
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Pages |
370–373 |
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Abstract |
This paper addresses the novel problem of characterizing conversational group dynamics. It is well documented in social psychology that depending on the objectives a group, the dynamics are different. For example, a competitive meeting has a different objective from that of a collaborative meeting. We propose a method to characterize group dynamics based on the joint description of a group members' aggregated acoustical nonverbal behaviour to classify two meeting datasets (one being cooperative-type and the other being competitive-type). We use 4.5 hours of real behavioural multi-party data and show that our methodology can achieve a classification rate of upto 100%. |
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Address |
New York, USA |
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ISSN |
1945-7871 |
ISBN |
978-1-4244-4290-4 |
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ICME |
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Notes |
OR;MV |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ JRG2009 |
Serial |
1217 |
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Permanent link to this record |
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Author |
Sergio Escalera; Eloi Puertas; Petia Radeva; Oriol Pujol |
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Title |
Multimodal laughter recognition in video conversations |
Type |
Conference Article |
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Year |
2009 |
Publication |
2nd IEEE Workshop on CVPR for Human communicative Behavior analysis |
Abbreviated Journal |
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Pages |
110–115 |
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Laughter detection is an important area of interest in the Affective Computing and Human-computer Interaction fields. In this paper, we propose a multi-modal methodology based on the fusion of audio and visual cues to deal with the laughter recognition problem in face-to-face conversations. The audio features are extracted from the spectogram and the video features are obtained estimating the mouth movement degree and using a smile and laughter classifier. Finally, the multi-modal cues are included in a sequential classifier. Results over videos from the public discussion blog of the New York Times show that both types of features perform better when considered together by the classifier. Moreover, the sequential methodology shows to significantly outperform the results obtained by an Adaboost classifier. |
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Address |
Miami (USA) |
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Series Editor |
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Edition |
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ISSN |
2160-7508 |
ISBN |
978-1-4244-3994-2 |
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Conference |
CVPR |
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Notes |
MILAB;HuPBA |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ EPR2009c |
Serial |
1188 |
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Permanent link to this record |
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Author |
Sergio Escalera; R. M. Martinez; Jordi Vitria; Petia Radeva; Maria Teresa Anguera |
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Title |
Dominance Detection in Face-to-face Conversations |
Type |
Conference Article |
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Year |
2009 |
Publication |
2nd IEEE Workshop on CVPR for Human communicative Behavior analysis |
Abbreviated Journal |
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Volume |
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Issue |
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Pages |
97–102 |
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Abstract |
Dominance is referred to the level of influence a person has in a conversation. Dominance is an important research area in social psychology, but the problem of its automatic estimation is a very recent topic in the contexts of social and wearable computing. In this paper, we focus on dominance detection from visual cues. We estimate the correlation among observers by categorizing the dominant people in a set of face-to-face conversations. Different dominance indicators from gestural communication are defined, manually annotated, and compared to the observers opinion. Moreover, the considered indicators are automatically extracted from video sequences and learnt by using binary classifiers. Results from the three analysis shows a high correlation and allows the categorization of dominant people in public discussion video sequences. |
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Miami, USA |
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2160-7508 |
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978-1-4244-3994-2 |
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CVPR |
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HuPBA; OR; MILAB;MV |
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BCNPCL @ bcnpcl @ EMV2009 |
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1227 |
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Enric Marti; Debora Gil; Marc Vivet; Carme Julia |
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Aprendizaje Basado en Proyectos en la asignatura de Gráficos por Computador en Ingeniería Informática. Balance de cuatro años de experiencia |
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Miscellaneous |
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2009 |
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15th Jornadas de Enseñanza Universitaria de la Informatica |
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Barcelona, Spain |
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1 |
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978-84-692-2758-9 |
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JENUI |
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IAM;ADAS |
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IAM @ iam @ MGV2009 |
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1596 |
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