DET: Efficient Pedestrian Detection Applied to People Observation
Due to the large volume of data obtained from surveillance cameras, the understanding and automatic interpretation of human activities in videos is of great interest in order to assist in the tasks of security agents. Among problems that need to be handled, pedestrian detection is essential so that the huge amounts of visual data captured by surveillance cameras is reduced to a volume that can be managed by current computing systems. Thus, the activities being performed by agents present in a scene can be analyzed. This project proposed the development of methods for pedestrian detection to reduce computational cost and maintain the accuracy of detectors.
Contributions generated from this research…
The Good, the Fast and the Better Pedestrian Detector Masters Thesis
Federal University of Minas Gerais, 2016.
In: Image Processing, IEEE Transactions on, 24 (12), pp. 4726-4740, 2015, ISSN: 1057-7149.
In: Workshop em Visao Computacional (WVC), pp. 1-8, 2015.
In: 14th Iberoamerican Congress on Pattern Recognition (CIARP), pp. 1-8, 2015.
In: Information Forensics and Security, IEEE Transactions on, 10 (4), pp. 864-879, 2015, ISSN: 1556-6013.
In: 19th Iberoamerican Congress on Pattern Recognition (CIARP), pp. 948-955, Springer International Publishing, 2014.
Workshop of Undergraduate Works (WUW) in SIBGRAPI - Conference on Graphics, Patterns and Images, 2014, (1st place award).
In: IAPR International Conference on Pattern Recognition (ICPR), pp. 1-6, 2014.
In: X Workshop de Visão Computacional, pp. 1-6, 2014.
Scalable Feature Extraction for Visual Surveillance Inproceedings
In: Iberoamerican Congress on Pattern Recognition (CIARP), pp. 375-382, Springer International Publishing, 2014.
In: Iberoamerican Congress on Pattern Recognition (CIARP), pp. 454-461, Springer International Publishing, 2014.