Large-Scale Event Detection Using Semi-Hidden Markov Models

Authors:
Somboon Hongeng;Ramakant Nevatia
Affiliations:
-;-
Venue:
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Year:
2003

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Abstract

We present a new approach to recognizing events invideos.We first detect and track moving objects in thescene.Based on the shape and motion properties ofthese objects, we infer probabilities of primitive eventsframe-by-frame by using Bayesian networks.Compositeevents, consisting of multiple primitive events, overextended periods of time are analyzed by using a hidden,semi-Markov finite state model.This results in morereliable event segmentation compared to the use of standardHMMs in noisy video sequences at the cost of someincrease in computational complexity.We describe ourapproach to reducing this complexity.We demonstratethe effectiveness of our algorithm using both real-worldand pertubed data.