Multi-Target Tracking in Video
Fabio Poiesi and Andrea Cavallaro, School of Electrical Engineering and Computer Science, Queen Mary University of London, UK
Abstract
Multi-target tracking in video helps in gathering information from motion patterns to describe behaviors (e.g., sport team formations), to detect events of interest (e.g., crossing streets in forbidden locations) and to facilitate content retrieval (e.g., automatic highlights generation). Several challenges affect multi-target tracking, including color and shape similarities, occlusions and abrupt motion variations. We define a generic flow diagram that we use to discuss and compare the main stages of multi-target trackers, namely feature extraction, target prediction, ...
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