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Author |
Sergio Escalera; Xavier Baro; Jordi Vitria; Petia Radeva; Bogdan Raducanu |
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Title |
Social Network Extraction and Analysis Based on Multimodal Dyadic Interaction |
Type |
Journal Article |
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Year |
2012 |
Publication |
Sensors |
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SENS |
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Volume |
12 |
Issue |
2 |
Pages |
1702-1719 |
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Abstract |
IF=1.77 (2010)
Social interactions are a very important component in peopleís lives. Social network analysis has become a common technique used to model and quantify the properties of social interactions. In this paper, we propose an integrated framework to explore the characteristics of a social network extracted from multimodal dyadic interactions. For our study, we used a set of videos belonging to New York Timesí Blogging Heads opinion blog.
The Social Network is represented as an oriented graph, whose directed links are determined by the Influence Model. The linksí weights are a measure of the ìinfluenceî a person has over the other. The states of the Influence Model encode automatically extracted audio/visual features from our videos using state-of-the art algorithms. Our results are reported in terms of accuracy of audio/visual data fusion for speaker segmentation and centrality measures used to characterize the extracted social network. |
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Molecular Diversity Preservation International |
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MILAB; OR;HuPBA;MV |
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no |
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Admin @ si @ EBV2012 |
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1885 |
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Author |
Fadi Dornaika; Alireza Bosaghzadeh; Bogdan Raducanu |
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Title |
LSDA Solution Schemes for Modelless 3D Head Pose Estimation |
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Conference Article |
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Year |
2012 |
Publication |
IEEE Workshop on the Applications of Computer Vision |
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393-398 |
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Breckenridge; USA; |
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WACV |
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OR;MV |
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no |
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Admin @ si @ DBR2012 |
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1889 |
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Author |
Bogdan Raducanu; Fadi Dornaika |
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Title |
Appearance-based Face Recognition Using A Supervised Manifold Learning Framework |
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Conference Article |
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Year |
2012 |
Publication |
IEEE Workshop on the Applications of Computer Vision |
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Pages |
465-470 |
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Many natural image sets, depicting objects whose appearance is changing due to motion, pose or light variations, can be considered samples of a low-dimension nonlinear manifold embedded in the high-dimensional observation space (the space of all possible images). The main contribution of our work is represented by a Supervised Laplacian Eigemaps (S-LE) algorithm, which exploits the class label information for mapping the original data in the embedded space. Our proposed approach benefits from two important properties: i) it is discriminative, and ii) it adaptively selects the neighbors of a sample without using any predefined neighborhood size. Experiments were conducted on four face databases and the results demonstrate that the proposed algorithm significantly outperforms many linear and non-linear embedding techniques. Although we've focused on the face recognition problem, the proposed approach could also be extended to other category of objects characterized by large variance in their appearance. |
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Breckenridge; CO; USA |
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IEEE Xplore |
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1550-5790 |
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978-1-4673-0233-3 |
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WACV |
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OR;MV |
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no |
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Admin @ si @ RaD2012d |
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1890 |
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Author |
Santiago Segui; Michal Drozdzal; Petia Radeva; Jordi Vitria |
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Title |
An Integrated Approach to Contextual Face Detection |
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Conference Article |
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Year |
2012 |
Publication |
1st International Conference on Pattern Recognition Applications and Methods |
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143-150 |
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Face detection is, in general, based on content-based detectors. Nevertheless, the face is a non-rigid object with well defined relations with respect to the human body parts. In this paper, we propose to take benefit of the context information in order to improve content-based face detections. We propose a novel framework for integrating multiple content- and context-based detectors in a discriminative way. Moreover, we develop an integrated scoring procedure that measures the ’faceness’ of each hypothesis and is used to discriminate the detection results. Our approach detects a higher rate of faces while minimizing the number of false detections, giving an average increase of more than 10% in average precision when comparing it to state-of-the art face detectors |
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Vilamoura, Algarve, Portugal |
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Springer |
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ICPRAM |
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Notes |
MILAB; OR;MV |
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no |
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Call Number |
Admin @ si @ SDR2012 |
Serial |
1895 |
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Author |
Carles Sanchez;F. Javier Sanchez; Antoni Rosell; Debora Gil |
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Title |
An illumination model of the trachea appearance in videobronchoscopy images |
Type |
Book Chapter |
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Year |
2012 |
Publication |
Image Analysis and Recognition |
Abbreviated Journal |
LNCS |
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Volume |
7325 |
Issue |
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Pages |
313-320 |
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Keywords |
Bronchoscopy, tracheal ring, stenosis assesment, trachea appearance model, segmentation |
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Abstract |
Videobronchoscopy is a medical imaging technique that allows interactive navigation inside the respiratory pathways. This imaging modality provides realistic images and allows non-invasive minimal intervention procedures. Tracheal procedures are routinary interventions that require assessment of the percentage of obstructed pathway for injury (stenosis) detection. Visual assessment in videobronchoscopic sequences requires high expertise of trachea anatomy and is prone to human error.
This paper introduces an automatic method for the estimation of steneosed trachea percentage reduction in videobronchoscopic images. We look for tracheal rings , whose deformation determines the degree of obstruction. For ring extraction , we present a ring detector based on an illumination and appearance model. This model allows us to parametrise the ring detection. Finally, we can infer optimal estimation parameters for any video resolution. |
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Address |
Aveiro, Portugal |
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Springer Berlin Heidelberg |
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Lecture Notes in Computer Science |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-31297-7 |
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800 |
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ICIAR |
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Notes |
MV;IAM |
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no |
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Call Number |
IAM @ iam @ SSR2012 |
Serial |
1898 |
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Author |
Patricia Marquez; Debora Gil ; Aura Hernandez-Sabate |
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Title |
Error Analysis for Lucas-Kanade Based Schemes |
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Conference Article |
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Year |
2012 |
Publication |
9th International Conference on Image Analysis and Recognition |
Abbreviated Journal |
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Volume |
7324 |
Issue |
I |
Pages |
184-191 |
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Keywords |
Optical flow, Confidence measure, Lucas-Kanade, Cardiac Magnetic Resonance |
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Abstract |
Optical flow is a valuable tool for motion analysis in medical imaging sequences. A reliable application requires determining the accuracy of the computed optical flow. This is a main challenge given the absence of ground truth in medical sequences. This paper presents an error analysis of Lucas-Kanade schemes in terms of intrinsic design errors and numerical stability of the algorithm. Our analysis provides a confidence measure that is naturally correlated to the accuracy of the flow field. Our experiments show the higher predictive value of our confidence measure compared to existing measures. |
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Aveiro, Portugal |
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Springer-Verlag Berlin Heidelberg |
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english |
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Campilho, Aurélio and Kamel, Mohamed |
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Lecture Notes in Computer Science |
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LNCS |
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0302-9743 |
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978-3-642-31294-6 |
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ICIAR |
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IAM |
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no |
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Call Number |
IAM @ iam @ MGH2012a |
Serial |
1899 |
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Author |
Albert Andaluz; Francesc Carreras; Cristina Santa Marta;Debora Gil |
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Title |
Myocardial torsion estimation with Tagged-MRI in the OsiriX platform |
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Conference Article |
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Year |
2012 |
Publication |
ISBI Workshop on Open Source Medical Image Analysis software |
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Myocardial torsion (MT) plays a crucial role in the assessment of the functionality of the
left ventricle. For this purpose, the IAM group at the CVC has developed the Harmonic Phase Flow (HPF) plugin for the Osirix DICOM platform . We have validated its funcionalty on sequences acquired using different protocols and including healthy and pathological cases. Results show similar torsion trends for SPAMM acquisitions, with pathological cases introducing expected deviations from the ground truth. Finally, we provide the plugin free of charge at http://iam.cvc.uab.es |
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Barcelona, Spain |
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IEEE |
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Editor |
Wiro Niessen (Erasmus MC) and Marc Modat (UCL) |
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ISBI |
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IAM |
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no |
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Call Number |
IAM @ iam @ ACS2012 |
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1900 |
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Author |
David Geronimo; Frederic Lerasle; Antonio Lopez |
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Title |
State-driven particle filter for multi-person tracking |
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Conference Article |
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Year |
2012 |
Publication |
11th International Conference on Advanced Concepts for Intelligent Vision Systems |
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Volume |
7517 |
Issue |
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Pages |
467-478 |
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Keywords |
human tracking |
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Abstract |
Multi-person tracking can be exploited in applications such as driver assistance, surveillance, multimedia and human-robot interaction. With the help of human detectors, particle filters offer a robust method able to filter noisy detections and provide temporal coherence. However, some traditional problems such as occlusions with other targets or the scene, temporal drifting or even the lost targets detection are rarely considered, making the systems performance decrease. Some authors propose to overcome these problems using heuristics not explained
and formalized in the papers, for instance by defining exceptions to the model updating depending on tracks overlapping. In this paper we propose to formalize these events by the use of a state-graph, defining the current state of the track (e.g., potential , tracked, occluded or lost) and the transitions between states in an explicit way. This approach has the advantage of linking track actions such as the online underlying models updating, which gives flexibility to the system. It provides an explicit representation to adapt the multiple parallel trackers depending on the context, i.e., each track can make use of a specific filtering strategy, dynamic model, number of particles, etc. depending on its state. We implement this technique in a single-camera multi-person tracker and test
it in public video sequences. |
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Brno, Chzech Republic |
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Springer |
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Heidelberg |
Editor |
J. Blanc-Talon et al. |
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English |
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ACIVS |
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ADAS |
Approved |
yes |
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Call Number |
GLL2012; ADAS @ adas @ gll2012a |
Serial |
1990 |
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Author |
Javier Marin; David Geronimo; David Vazquez; Antonio Lopez |
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Title |
Pedestrian Detection: Exploring Virtual Worlds |
Type |
Book Chapter |
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Year |
2012 |
Publication |
Handbook of Pattern Recognition: Methods and Application |
Abbreviated Journal |
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5 |
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145-162 |
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Keywords |
Virtual worlds; Pedestrian Detection; Domain Adaptation |
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Abstract |
Handbook of pattern recognition will include contributions from university educators and active research experts. This Handbook is intended to serve as a basic reference on methods and applications of pattern recognition. The primary aim of this handbook is providing the community of pattern recognition with a readable, easy to understand resource that covers introductory, intermediate and advanced topics with equal clarity. Therefore, the Handbook of pattern recognition can serve equally well as reference resource and as classroom textbook. Contributions cover all methods, techniques and applications of pattern recognition. A tentative list of relevant topics might include: 1- Statistical, structural, syntactic pattern recognition. 2- Neural networks, machine learning, data mining. 3- Discrete geometry, algebraic, graph-based techniques for pattern recognition. 4- Face recognition, Signal analysis, image coding and processing, shape and texture analysis. 5- Document processing, text and graphics recognition, digital libraries. 6- Speech recognition, music analysis, multimedia systems. 7- Natural language analysis, information retrieval. 8- Biometrics, biomedical pattern analysis and information systems. 9- Other scientific, engineering, social and economical applications of pattern recognition. 10- Special hardware architectures, software packages for pattern recognition. |
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iConcept Press |
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English |
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978-1-477554-82-1 |
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ADAS |
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no |
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ADAS @ adas @ MGV2012 |
Serial |
1979 |
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Author |
Sergio Escalera; Josep Moya; Laura Igual; Veronica Violant; Maria Teresa Anguera |
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Title |
Automatic Human Behavior Analysis in ADHD |
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Conference Article |
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2012 |
Publication |
Eunethydis 2nd International ADHD Conference |
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Poster |
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EUNETHYDIS |
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MILAB;HuPBA |
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no |
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Admin @ si @ EMI2012a |
Serial |
2058 |
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Author |
Lluis Gomez |
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Title |
Perceptual Organization for Text Extraction in Natural Scenes |
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Report |
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2012 |
Publication |
CVC Technical Report |
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173 |
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Bellaterra |
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Master's thesis |
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DAG |
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no |
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Admin @ si @ Gom2012 |
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2309 |
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Author |
Yainuvis Socarras; David Vazquez; Antonio Lopez; David Geronimo; Theo Gevers |
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Title |
Improving HOG with Image Segmentation: Application to Human Detection |
Type |
Conference Article |
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Year |
2012 |
Publication |
11th International Conference on Advanced Concepts for Intelligent Vision Systems |
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7517 |
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178-189 |
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Segmentation; Pedestrian Detection |
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Abstract |
In this paper we improve the histogram of oriented gradients (HOG), a core descriptor of state-of-the-art object detection, by the use of higher-level information coming from image segmentation. The idea is to re-weight the descriptor while computing it without increasing its size. The benefits of the proposal are two-fold: (i) to improve the performance of the detector by enriching the descriptor information and (ii) take advantage of the information of image segmentation, which in fact is likely to be used in other stages of the detection system such as candidate generation or refinement.
We test our technique in the INRIA person dataset, which was originally developed to test HOG, embedding it in a human detection system. The well-known segmentation method, mean-shift (from smaller to larger super-pixels), and different methods to re-weight the original descriptor (constant, region-luminance, color or texture-dependent) has been evaluated. We achieve performance improvements of 4:47% in detection rate through the use of differences of color between contour pixel neighborhoods as re-weighting function. |
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Brno, Czech Republic |
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Springer Berlin Heidelberg |
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Editor |
J. Blanc-Talon et al. |
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English |
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LNCS |
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0302-9743 |
ISBN |
978-3-642-33139-8 |
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ACIVS |
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ADAS;ISE |
Approved |
no |
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ADAS @ adas @ SLV2012 |
Serial |
1980 |
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Author |
David Vazquez; Antonio Lopez; Daniel Ponsa |
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Title |
Unsupervised Domain Adaptation of Virtual and Real Worlds for Pedestrian Detection |
Type |
Conference Article |
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Year |
2012 |
Publication |
21st International Conference on Pattern Recognition |
Abbreviated Journal |
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3492 - 3495 |
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Pedestrian Detection; Domain Adaptation; Virtual worlds |
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Abstract |
Vision-based object detectors are crucial for different applications. They rely on learnt object models. Ideally, we would like to deploy our vision system in the scenario where it must operate, and lead it to self-learn how to distinguish the objects of interest, i.e., without human intervention. However, the learning of each object model requires labelled samples collected through a tiresome manual process. For instance, we are interested in exploring the self-training of a pedestrian detector for driver assistance systems. Our first approach to avoid manual labelling consisted in the use of samples coming from realistic computer graphics, so that their labels are automatically available [12]. This would make possible the desired self-training of our pedestrian detector. However, as we showed in [14], between virtual and real worlds it may be a dataset shift. In order to overcome it, we propose the use of unsupervised domain adaptation techniques that avoid human intervention during the adaptation process. In particular, this paper explores the use of the transductive SVM (T-SVM) learning algorithm in order to adapt virtual and real worlds for pedestrian detection (Fig. 1). |
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Address |
Tsukuba Science City, Japan |
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IEEE |
Place of Publication |
Tsukuba Science City, JAPAN |
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ISSN |
1051-4651 |
ISBN |
978-1-4673-2216-4 |
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ICPR |
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ADAS |
Approved |
no |
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Call Number |
ADAS @ adas @ VLP2012 |
Serial |
1981 |
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Permanent link to this record |
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Author |
Jon Almazan; Alicia Fornes; Ernest Valveny |
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Title |
A non-rigid appearance model for shape description and recognition |
Type |
Journal Article |
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Year |
2012 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
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Volume |
45 |
Issue |
9 |
Pages |
3105--3113 |
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Keywords |
Shape recognition; Deformable models; Shape modeling; Hand-drawn recognition |
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Abstract |
In this paper we describe a framework to learn a model of shape variability in a set of patterns. The framework is based on the Active Appearance Model (AAM) and permits to combine shape deformations with appearance variability. We have used two modifications of the Blurred Shape Model (BSM) descriptor as basic shape and appearance features to learn the model. These modifications permit to overcome the rigidity of the original BSM, adapting it to the deformations of the shape to be represented. We have applied this framework to representation and classification of handwritten digits and symbols. We show that results of the proposed methodology outperform the original BSM approach. |
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0031-3203 |
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DAG @ dag @ AFV2012 |
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1982 |
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Author |
Jon Almazan; David Fernandez; Alicia Fornes; Josep Llados; Ernest Valveny |
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Title |
A Coarse-to-Fine Approach for Handwritten Word Spotting in Large Scale Historical Documents Collection |
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Conference Article |
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Year |
2012 |
Publication |
13th International Conference on Frontiers in Handwriting Recognition |
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453-458 |
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In this paper we propose an approach for word spotting in handwritten document images. We state the problem from a focused retrieval perspective, i.e. locating instances of a query word in a large scale dataset of digitized manuscripts. We combine two approaches, namely one based on word segmentation and another one segmentation-free. The first approach uses a hashing strategy to coarsely prune word images that are unlikely to be instances of the query word. This process is fast but has a low precision due to the errors introduced in the segmentation step. The regions containing candidate words are sent to the second process based on a state of the art technique from the visual object detection field. This discriminative model represents the appearance of the query word and computes a similarity score. In this way we propose a coarse-to-fine approach achieving a compromise between efficiency and accuracy. The validation of the model is shown using a collection of old handwritten manuscripts. We appreciate a substantial improvement in terms of precision regarding the previous proposed method with a low computational cost increase. |
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978-1-4673-2262-1 |
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ICFHR |
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DAG @ dag @ AFF2012 |
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1983 |
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