A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature Detection with Automatic Scale Selection
International Journal of Computer Vision
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Histogram of oriented rectangles: A new pose descriptor for human action recognition
Image and Vision Computing
Stereo-MAS: Multi-Agent System for Image Stereo Processing
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
Human detection using oriented histograms of flow and appearance
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
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This paper presents a Multi-Agent System (MAS) that implements techniques of Computer Vision for processing stereoscopic images by using stereo cameras The MAS focuses on detecting people and their behavior through a two-phase method In the first phase, the MAS creates a model of the environment by using a disparity map It can be constructed in real time, even if there are moving objects in the area (such as people passing by) In the second phase, the MAS is able to detect people and their behavior by combining a series of techniques such as Sum of Absolute Differences (SAD) or Gradient Orientation Histograms (HOG) The preliminary results and conclusions after several experiments performed on real scenarios are described in this paper.