People detection in image and video data

Authors:
Supriya Rao;N. C. Pramod;Chaitanya Krishna Paturu
Affiliations:
Honeywell Technology Solutions, Bangalore, India;Honeywell Technology Solutions, Bangalore, India;Honeywell Technology Solutions, Bangalore, India
Venue:
VNBA '08 Proceedings of the 1st ACM workshop on Vision networks for behavior analysis
Year:
2008

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Abstract

In this paper, we address the problem of people detection in real world videos/images. We propose an approach that combines a generative model with a discriminative model to utilize the advantages of both types of detections. The individual body parts of the person are detected based on discriminative approach and the evidence aggregation from part detectors is done in a generative model by incorporating a probability framework. The algorithm works on images that can be extended to video data also. The advantage of this framework is that it can handle occlusions and crowded scenarios, where motion information is ambiguous. The results obtained illustrate the ability of the algorithm to give good detection rates despite occlusions, poor illumination conditions and pose, scale variations of people in the scene.