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Author |
David Geronimo; Frederic Lerasle; Antonio Lopez |
![download PDF file pdf](img/file_PDF.gif)
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Title |
State-driven particle filter for multi-person tracking |
Type |
Conference Article |
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Year |
2012 |
Publication |
11th International Conference on Advanced Concepts for Intelligent Vision Systems |
Abbreviated Journal |
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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 |
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J. Blanc-Talon et al. |
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English |
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ACIVS |
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ADAS |
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yes |
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Call Number |
GLL2012; ADAS @ adas @ gll2012a |
Serial |
1990 |
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Author |
Fadi Dornaika; Bogdan Raducanu |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Analysis and Recognition of Facial Expressions in Videos Using Facial Shape Deformation |
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Book Chapter |
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Year |
2012 |
Publication |
Facial Expressions: Dynamic Patterns, Impairments and Social Perceptions |
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157-178 |
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NOVA Publishers |
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Editor |
S.E. Carter |
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OR;MV |
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no |
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Call Number |
Admin @ si @ DoR2012 |
Serial |
2183 |
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Author |
Sergio Escalera; Xavier Baro; Jordi Vitria; Petia Radeva; Bogdan Raducanu |
![download PDF file pdf](img/file_PDF.gif)
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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 |
Abbreviated Journal |
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 |
David Roche; Debora Gil; Jesus Giraldo |
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Title |
Assessing agonist efficacy in an uncertain Em world |
Type |
Conference Article |
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Year |
2012 |
Publication |
40th Keystone Symposia on mollecular and celular biology |
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Pages |
79 |
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The operational model of agonism has been widely used for the analysis of agonist action since its formulation in 1983. The model includes the Em parameter, which is defined as the maximum response of the system. The methods for Em estimation provide Em values not significantly higher than the maximum responses achieved by full agonists. However, it has been found that that some classes of compounds as, for instance, superagonists and positive allosteric modulators can increase the full agonist maximum response, implying upper limits for Em and thereby posing doubts on the validity of Em estimates. Because of the correlation between Em and operational efficacy, τ, wrong Em estimates will yield wrong τ estimates.
In this presentation, the operational model of agonism and various methods for the simulation of allosteric modulation will be analyzed. Alternatives for curve fitting will be presented and discussed. |
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Fairmont Banff Springs, Banff, Alberta, Canada |
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Keystone Symposia |
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Keystone Symposia |
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Editor |
A. Christopoulus and M. Bouvier |
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english |
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english |
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Keystone Symposia |
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KSMCB |
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IAM |
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no |
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Call Number |
IAM @ iam @ RGG2012 |
Serial |
1855 |
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Author |
Joost Van de Weijer; Robert Benavente; Maria Vanrell; Cordelia Schmid; Ramon Baldrich; Jacob Verbeek; Diane Larlus |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Color Naming |
Type |
Book Chapter |
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Year |
2012 |
Publication |
Color in Computer Vision: Fundamentals and Applications |
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Issue |
17 |
Pages |
287-317 |
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John Wiley & Sons, Ltd. |
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Theo Gevers;Arjan Gijsenij;Joost Van de Weijer;Jan-Mark Geusebroek |
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CIC |
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no |
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Admin @ si @ WBV2012 |
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2063 |
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Author |
Aura Hernandez-Sabate; Debora Gil |
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Title |
The Benefits of IVUS Dynamics for Retrieving Stable Models of Arteries |
Type |
Book Chapter |
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Year |
2012 |
Publication |
Intravascular Ultrasound |
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Pages |
185-206 |
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Publisher ![sorted by Publisher field, descending order (down)](img/sort_desc.gif) |
Intech |
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Editor |
Yasuhiro Honda |
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English |
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english |
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978-953-307-900-4 |
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IAM; ADAS |
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no |
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Call Number |
IAM @ iam @ HeG2012 |
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1684 |
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Author |
Alicia Fornes; Josep Llados; Gemma Sanchez; Horst Bunke |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Writer Identification in Old Handwritten Music Scores |
Type |
Book Chapter |
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Year |
2012 |
Publication |
Pattern Recognition and Signal Processing in Archaeometry: Mathematical and Computational Solutions for Archaeology |
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27-63 |
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Abstract |
The aim of writer identification is determining the writer of a piece of handwriting from a set of writers. In this paper we present a system for writer identification in old handwritten music scores. Even though an important amount of compositions contains handwritten text in the music scores, the aim of our work is to use only music notation to determine the author. The steps of the system proposed are the following. First of all, the music sheet is preprocessed and normalized for obtaining a single binarized music line, without the staff lines. Afterwards, 100 features are extracted for every music line, which are subsequently used in a k-NN classifier that compares every feature vector with prototypes stored in a database. By applying feature selection and extraction methods on the original feature set, the performance is increased. The proposed method has been tested on a database of old music scores from the 17th to 19th centuries, achieving a recognition rate of about 95%. |
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IGI-Global |
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Editor |
Copnstantin Papaodysseus |
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DAG |
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no |
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Call Number |
Admin @ si @ FLS2012 |
Serial |
1828 |
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Permanent link to this record |
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Author |
Xavier Perez Sala; Laura Igual; Sergio Escalera; Cecilio Angulo |
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Title |
Uniform Sampling of Rotations for Discrete and Continuous Learning of 2D Shape Models |
Type |
Book Chapter |
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Year |
2012 |
Publication |
Vision Robotics: Technologies for Machine Learning and Vision Applications |
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2 |
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23-42 |
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Abstract |
Different methodologies of uniform sampling over the rotation group, SO(3), for building unbiased 2D shape models from 3D objects are introduced and reviewed in this chapter. State-of-the-art non uniform sampling approaches are discussed, and uniform sampling methods using Euler angles and quaternions are introduced. Moreover, since presented work is oriented to model building applications, it is not limited to general discrete methods to obtain uniform 3D rotations, but also from a continuous point of view in the case of Procrustes Analysis. |
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IGI-Global |
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MILAB;HuPBA |
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no |
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Admin @ si @ PIE2012 |
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2064 |
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Permanent link to this record |
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Author |
Antonio Hernandez; Nadezhda Zlateva; Alexander Marinov; Miguel Reyes; Petia Radeva; Dimo Dimov; Sergio Escalera |
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Title |
Graph Cuts Optimization for Multi-Limb Human Segmentation in Depth Maps |
Type |
Conference Article |
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Year |
2012 |
Publication |
25th IEEE Conference on Computer Vision and Pattern Recognition |
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Pages |
726-732 |
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We present a generic framework for object segmentation using depth maps based on Random Forest and Graph-cuts theory, and apply it to the segmentation of human limbs in depth maps. First, from a set of random depth features, Random Forest is used to infer a set of label probabilities for each data sample. This vector of probabilities is used as unary term in α-β swap Graph-cuts algorithm. Moreover, depth of spatio-temporal neighboring data points are used as boundary potentials. Results on a new multi-label human depth data set show high performance in terms of segmentation overlapping of the novel methodology compared to classical approaches. |
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Portland; Oregon; June 2013 |
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IEEE Xplore |
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1063-6919 |
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978-1-4673-1226-4 |
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CVPR |
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Notes |
MILAB;HuPBA |
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no |
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Admin @ si @ HZM2012b |
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2046 |
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Author |
Fahad Shahbaz Khan; Muhammad Anwer Rao; Joost Van de Weijer; Andrew Bagdanov; Maria Vanrell; Antonio Lopez |
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Title |
Color Attributes for Object Detection |
Type |
Conference Article |
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Year |
2012 |
Publication |
25th IEEE Conference on Computer Vision and Pattern Recognition |
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3306-3313 |
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pedestrian detection |
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Abstract |
State-of-the-art object detectors typically use shape information as a low level feature representation to capture the local structure of an object. This paper shows that early fusion of shape and color, as is popular in image classification,
leads to a significant drop in performance for object detection. Moreover, such approaches also yields suboptimal results for object categories with varying importance of color and shape.
In this paper we propose the use of color attributes as an explicit color representation for object detection. Color attributes are compact, computationally efficient, and when combined with traditional shape features provide state-ofthe-
art results for object detection. Our method is tested on the PASCAL VOC 2007 and 2009 datasets and results clearly show that our method improves over state-of-the-art techniques despite its simplicity. We also introduce a new dataset consisting of cartoon character images in which color plays a pivotal role. On this dataset, our approach yields a significant gain of 14% in mean AP over conventional state-of-the-art methods. |
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Providence; Rhode Island; USA; |
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IEEE Xplore |
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1063-6919 |
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978-1-4673-1226-4 |
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CVPR |
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ADAS; CIC; |
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no |
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Admin @ si @ KRW2012 |
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1935 |
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Author |
Bogdan Raducanu; Fadi Dornaika |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Appearance-based Face Recognition Using A Supervised Manifold Learning Framework |
Type |
Conference Article |
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Year |
2012 |
Publication |
IEEE Workshop on the Applications of Computer Vision |
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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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Permanent link to this record |
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Author |
Diego Cheda; Daniel Ponsa; Antonio Lopez |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Pedestrian Candidates Generation using Monocular Cues |
Type |
Conference Article |
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Year |
2012 |
Publication |
IEEE Intelligent Vehicles Symposium |
Abbreviated Journal |
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7-12 |
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pedestrian detection |
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Abstract |
Common techniques for pedestrian candidates generation (e.g., sliding window approaches) are based on an exhaustive search over the image. This implies that the number of windows produced is huge, which translates into a significant time consumption in the classification stage. In this paper, we propose a method that significantly reduces the number of windows to be considered by a classifier. Our method is a monocular one that exploits geometric and depth information available on single images. Both representations of the world are fused together to generate pedestrian candidates based on an underlying model which is focused only on objects standing vertically on the ground plane and having certain height, according with their depths on the scene. We evaluate our algorithm on a challenging dataset and demonstrate its application for pedestrian detection, where a considerable reduction in the number of candidate windows is reached. |
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IEEE Xplore |
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1931-0587 |
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978-1-4673-2119-8 |
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IV |
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ADAS |
Approved |
no |
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Call Number |
Admin @ si @ CPL2012c; ADAS @ adas @ cpl2012d |
Serial |
2013 |
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Permanent link to this record |
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Author |
Naveen Onkarappa; Angel Sappa |
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Title |
An Empirical Study on Optical Flow Accuracy Depending on Vehicle Speed |
Type |
Conference Article |
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Year |
2012 |
Publication |
IEEE Intelligent Vehicles Symposium |
Abbreviated Journal |
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1138-1143 |
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Abstract |
Driver assistance and safety systems are getting attention nowadays towards automatic navigation and safety. Optical flow as a motion estimation technique has got major roll in making these systems a reality. Towards this, in the current paper, the suitability of polar representation for optical flow estimation in such systems is demonstrated. Furthermore, the influence of individual regularization terms on the accuracy of optical flow on image sequences of different speeds is empirically evaluated. Also a new synthetic dataset of image sequences with different speeds is generated along with the ground-truth optical flow. |
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Alcalá de Henares |
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IEEE Xplore |
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1931-0587 |
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978-1-4673-2119-8 |
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IV |
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ADAS |
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no |
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Admin @ si @ NaS2012 |
Serial |
2020 |
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Author |
Miguel Oliveira; Angel Sappa; V. Santos |
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Title |
Color Correction for Onboard Multi-camera Systems using 3D Gaussian Mixture Models |
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Conference Article |
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Year |
2012 |
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IEEE Intelligent Vehicles Symposium |
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299-303 |
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The current paper proposes a novel color correction approach for onboard multi-camera systems. It works by segmenting the given images into several regions. A probabilistic segmentation framework, using 3D Gaussian Mixture Models, is proposed. Regions are used to compute local color correction functions, which are then combined to obtain the final corrected image. An image data set of road scenarios is used to establish a performance comparison of the proposed method with other seven well known color correction algorithms. Results show that the proposed approach is the highest scoring color correction method. Also, the proposed single step 3D color space probabilistic segmentation reduces processing time over similar approaches. |
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Alcalá de Henares |
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IEEE Xplore |
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1931-0587 |
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978-1-4673-2119-8 |
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IV |
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ADAS |
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no |
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Admin @ si @ OSS2012b |
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2021 |
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Author |
Naila Murray; Luca Marchesotti; Florent Perronnin |
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Title |
AVA: A Large-Scale Database for Aesthetic Visual Analysis |
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Conference Article |
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Year |
2012 |
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25th IEEE Conference on Computer Vision and Pattern Recognition |
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2408-2415 |
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Abstract |
With the ever-expanding volume of visual content available, the ability to organize and navigate such content by aesthetic preference is becoming increasingly important. While still in its nascent stage, research into computational models of aesthetic preference already shows great potential. However, to advance research, realistic, diverse and challenging databases are needed. To this end, we introduce a new large-scale database for conducting Aesthetic Visual Analysis: AVA. It contains over 250,000 images along with a rich variety of meta-data including a large number of aesthetic scores for each image, semantic labels for over 60 categories as well as labels related to photographic style. We show the advantages of AVA with respect to existing databases in terms of scale, diversity, and heterogeneity of annotations. We then describe several key insights into aesthetic preference afforded by AVA. Finally, we demonstrate, through three applications, how the large scale of AVA can be leveraged to improve performance on existing preference tasks |
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Providence, Rhode Islan |
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1063-6919 |
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978-1-4673-1226-4 |
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CVPR |
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CIC |
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no |
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Call Number |
Admin @ si @ MMP2012a |
Serial |
2025 |
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