Occluded Pedestrian Tracking Using Body-Part Tracklets

Detection of pedestrians under occlusion has been addressed previously with body-part-based approaches, in particular using the generalised Hough transform. Tracking is usually addressed by first detecting pedestrians in each frame independently and then tracking the detections over time. This paper...

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Bibliographic Details
Published in2010 International Conference on Digital Image Computing: Techniques and Applications pp. 314 - 319
Main Author Sherrah, J
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2010
Subjects
Detectors
Feature extraction
feature tracking
generalised Hough transform
Optimization
pedestrian tracking
tracklets
Training
Transforms
Uncertainty
Viterbi algorithm
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Summary:Detection of pedestrians under occlusion has been addressed previously with body-part-based approaches, in particular using the generalised Hough transform. Tracking is usually addressed by first detecting pedestrians in each frame independently and then tracking the detections over time. This paper presents a novel variation on the generalised Hough approach: tracking is performed first, and detection second. Robust features on a pedestrian are tracked over short time-frames to form tracklets. Not only do tracklets reduce false alarms due to unstable features, but they provide temporal correspondence information in Hough space. Consequently tracking can be posed as optimal path finding in Hough space and efficiently solved using the Viterbi algorithm. The paper also presents an improvement to the random Hough forest training method by using multi-objective optimisation.
ISBN:9781424488162
1424488168
DOI:10.1109/DICTA.2010.61