Artur Jordao The Good, the Fast and the Better Pedestrian Detector Masters Thesis Federal University of Minas Gerais, 2016. @mastersthesis{Jordao:2016:MSc,
title = {The Good, the Fast and the Better Pedestrian Detector},
author = {Artur Jordao},
url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/03/dissertation_2016_ArturJordao.pdf},
year = {2016},
date = {2016-06-24},
school = {Federal University of Minas Gerais},
abstract = {Pedestrian detection is a well-known problem in Computer Vision, mostly because of its direct applications in surveillance, transit safety and robotics. In the past decade, several efforts have been performed to improve the detection in terms of accuracy, speed and feature enhancement. In this work, we propose and analyze techniques focusing on these points. First, we develop an accurate oblique random forest (oRF) associated with Partial Least Squares (PLS). The method utilizes the PLS to find a decision surface, at each node of a decision tree, that better splits the samples presented to it, based on some purity criterion. To measure the advantages provided by PLS on the oRF, we compare the proposed method with the oRF based on SVM. Second, we evaluate and compare filtering approaches to reduce the search space and keep only potential regions of interest to be presented to detectors, speeding up the detection process. Experimental results demonstrate that the evaluated filters are able to discard a large number of detection windows without compromising the accuracy. Finally, we propose a novel approach to extract powerful features regarding the scene. The method combines results of distinct pedestrian detectors by reinforcing the human hypothesis, whereas suppressing a significant number of false positives due to the lack of spatial consensus when multiple detectors are considered. Our proposed approach, referred to as Spatial Consensus (SC), outperforms all previously published state-of-the-art pedestrian detection methods.},
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pubstate = {published},
tppubtype = {mastersthesis}
}
Pedestrian detection is a well-known problem in Computer Vision, mostly because of its direct applications in surveillance, transit safety and robotics. In the past decade, several efforts have been performed to improve the detection in terms of accuracy, speed and feature enhancement. In this work, we propose and analyze techniques focusing on these points. First, we develop an accurate oblique random forest (oRF) associated with Partial Least Squares (PLS). The method utilizes the PLS to find a decision surface, at each node of a decision tree, that better splits the samples presented to it, based on some purity criterion. To measure the advantages provided by PLS on the oRF, we compare the proposed method with the oRF based on SVM. Second, we evaluate and compare filtering approaches to reduce the search space and keep only potential regions of interest to be presented to detectors, speeding up the detection process. Experimental results demonstrate that the evaluated filters are able to discard a large number of detection windows without compromising the accuracy. Finally, we propose a novel approach to extract powerful features regarding the scene. The method combines results of distinct pedestrian detectors by reinforcing the human hypothesis, whereas suppressing a significant number of false positives due to the lack of spatial consensus when multiple detectors are considered. Our proposed approach, referred to as Spatial Consensus (SC), outperforms all previously published state-of-the-art pedestrian detection methods. |
A Pinto; H Pedrini; William Robson Schwartz; Rocha A Face Spoofing Detection Through Visual Codebooks of Spectral Temporal Cubes Journal Article Em: Image Processing, IEEE Transactions on, 24 (12), pp. 4726-4740, 2015, ISSN: 1057-7149. @article{TIP:2015:Pinto,
title = {Face Spoofing Detection Through Visual Codebooks of Spectral Temporal Cubes},
author = {A Pinto and H Pedrini and William Robson Schwartz and Rocha A},
url = {http://dx.doi.org/10.1109/TIP.2015.2466088},
issn = {1057-7149},
year = {2015},
date = {2015-01-01},
journal = {Image Processing, IEEE Transactions on},
volume = {24},
number = {12},
pages = {4726-4740},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Artur Jordao; Victor Hugo Cunha de Melo; William Robson Schwartz A Study of Filtering Approaches for Sliding Window Pedestrian Detection Inproceedings Em: Workshop em Visao Computacional (WVC), pp. 1-8, 2015. @inproceedings{Correia:2015:WVC,
title = {A Study of Filtering Approaches for Sliding Window Pedestrian Detection},
author = {Artur Jordao and Victor Hugo Cunha de Melo and William Robson Schwartz},
url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/paper_2015_WVC_Correia.pdf},
year = {2015},
date = {2015-01-01},
booktitle = {Workshop em Visao Computacional (WVC)},
pages = {1-8},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Ramon F Pessoa; William Robson Schwartz; Jefersson A dos Santos A Study on Low-Cost Representations for Image Feature Extraction on Mobile Devices Inproceedings Em: 14th Iberoamerican Congress on Pattern Recognition (CIARP), pp. 1-8, 2015. @inproceedings{Pessoa:2015:CIARP,
title = {A Study on Low-Cost Representations for Image Feature Extraction on Mobile Devices},
author = {Ramon F Pessoa and William Robson Schwartz and Jefersson A dos Santos},
url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/paper_2015_CIARP_Pessoa.pdf},
year = {2015},
date = {2015-01-01},
booktitle = {14th Iberoamerican Congress on Pattern Recognition (CIARP)},
pages = {1-8},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
|
D Menotti; G Chiachia; A Pinto; William Robson Schwartz; H Pedrini; Xavier A Falcao; A Rocha Deep Representations for Iris, Face, and Fingerprint Spoofing Detection Journal Article Em: Information Forensics and Security, IEEE Transactions on, 10 (4), pp. 864-879, 2015, ISSN: 1556-6013. @article{Menotti:2015:TIFS,
title = {Deep Representations for Iris, Face, and Fingerprint Spoofing Detection},
author = {D Menotti and G Chiachia and A Pinto and William Robson Schwartz and H Pedrini and Xavier A Falcao and A Rocha},
url = {http://dx.doi.org/10.1109/TIFS.2015.2398817},
issn = {1556-6013},
year = {2015},
date = {2015-01-01},
journal = {Information Forensics and Security, IEEE Transactions on},
volume = {10},
number = {4},
pages = {864-879},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Rensso Victor Hugo Mora Colque; Guillermo Camara Chavez; William Robson Schwartz Detection of groups of people in surveillance videos based on spatio-temporal clues Inproceedings Em: 19th Iberoamerican Congress on Pattern Recognition (CIARP), pp. 948-955, Springer International Publishing, 2014. @inproceedings{crowdciarp2014,
title = {Detection of groups of people in surveillance videos based on spatio-temporal clues},
author = {Rensso Victor Hugo Mora Colque and Guillermo Camara Chavez and William Robson Schwartz},
url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/2014-Detection-of-Groups-of-People-in-Surveillance-Videos-based-on-Spatio-Temporal-Clues.pdf},
year = {2014},
date = {2014-11-06},
booktitle = {19th Iberoamerican Congress on Pattern Recognition (CIARP)},
volume = {8827},
pages = {948-955},
publisher = {Springer International Publishing},
series = {Lecture Notes in Computer Science},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Jessica Sena; Cesar Augusto Moura Ferreira; Cassio Elias Santos dos Junior; Victor Hugo Cunha de Melo; William Robson Schwartz Self-Organizing Traffic Lights: A Pedestrian Oriented Approach Miscellaneous Workshop of Undergraduate Works (WUW) in SIBGRAPI - Conference on Graphics, Patterns and Images, 2014, (1st place award). @misc{sibgrapi2014selfb,
title = {Self-Organizing Traffic Lights: A Pedestrian Oriented Approach},
author = {Jessica Sena and Cesar Augusto Moura Ferreira and Cassio Elias Santos dos Junior and Victor Hugo Cunha de Melo and William Robson Schwartz},
url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/2014-SIBGRAPI-Self-Organizing-Traffic-Lights-A-Pedestrian-Oriented-Approach.pdf
http://www.icex.ufmg.br/index.php/noticias/noticias-do-icex/80-noticias-do-icex/alunos-do-dcc-sao-premiados-no-sibgrapi-2014},
year = {2014},
date = {2014-08-29},
pages = {86-91},
howpublished = {Workshop of Undergraduate Works (WUW) in SIBGRAPI - Conference on Graphics, Patterns and Images},
note = {1st place award},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
|
Victor Hugo Cunha de Melo; Samir Moreira Andrade Leao; D Menotti; William Robson Schwartz An Optimized Sliding Window Approach to Pedestrian Detection Inproceedings Em: IAPR International Conference on Pattern Recognition (ICPR), pp. 1-6, 2014. @inproceedings{Melo:2014:ICPR,
title = {An Optimized Sliding Window Approach to Pedestrian Detection},
author = {Victor Hugo Cunha de Melo and Samir Moreira Andrade Leao and D Menotti and William Robson Schwartz},
url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/2014-An-Optimized-Sliding-Window-Approach-to-Pedestrian-Detection.pdf},
year = {2014},
date = {2014-01-01},
booktitle = {IAPR International Conference on Pattern Recognition (ICPR)},
pages = {1-6},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Jessica Sena; Cesar Augusto Moura Ferreira; Cassio Elias Santos dos Junior; Victor Hugo Cunha de Melo; William Robson Schwartz Self-Organizing Traffic Lights: A Pedestrian Oriented Approach Inproceedings Em: X Workshop de Visão Computacional, pp. 1-6, 2014. @inproceedings{wvc2014self,
title = {Self-Organizing Traffic Lights: A Pedestrian Oriented Approach},
author = {Jessica Sena and Cesar Augusto Moura Ferreira and Cassio Elias Santos dos Junior and Victor Hugo Cunha de Melo and William Robson Schwartz},
url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/2014-WVC-Self-Organizing-Traffic-Lights-A-Pedestrian-Oriented-Approach.pdf},
year = {2014},
date = {2014-01-01},
booktitle = {X Workshop de Visão Computacional},
pages = {1-6},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Antonio Carlos Nazare Junior; Renato Ferreira; William Robson Schwartz Scalable Feature Extraction for Visual Surveillance Inproceedings Em: Iberoamerican Congress on Pattern Recognition (CIARP), pp. 375-382, Springer International Publishing, 2014. @inproceedings{Nazare:2014:CIARP,
title = {Scalable Feature Extraction for Visual Surveillance},
author = {Antonio Carlos Nazare Junior and Renato Ferreira and William Robson Schwartz},
url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/paper_2014_CIARP_Antonio.pdf},
year = {2014},
date = {2014-01-01},
booktitle = {Iberoamerican Congress on Pattern Recognition (CIARP)},
volume = {8827},
pages = {375-382},
publisher = {Springer International Publishing},
series = {Lecture Notes in Computer Science},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Raphael Felipe Carvalho de Prates; G Camara-Chavez; William Robson Schwartz; D M Gomes An Adaptive Vehicle License Plate Detection at Higher Matching Degree Inproceedings Em: Iberoamerican Congress on Pattern Recognition (CIARP), pp. 454-461, Springer International Publishing, 2014. @inproceedings{Prates:2014:CIARP,
title = {An Adaptive Vehicle License Plate Detection at Higher Matching Degree},
author = {Raphael Felipe Carvalho de Prates and G Camara-Chavez and William Robson Schwartz and D M Gomes},
url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/paper_2014_CIARP_Prates-1.pdf},
year = {2014},
date = {2014-01-01},
booktitle = {Iberoamerican Congress on Pattern Recognition (CIARP)},
volume = {8827},
pages = {454-461},
publisher = {Springer International Publishing},
series = {Lecture Notes in Computer Science},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
|
