TY - GEN
T1 - Particle filter with analytical inference for human body tracking
AU - Lee, Mun Wai
AU - Cohen, I.
AU - Jung, Soon Ki
N1 - Publisher Copyright:
© 2002 IEEE.
PY - 2002
Y1 - 2002
N2 - The paper introduces a framework that integrates analytical inference into the particle filtering scheme for human body tracking. The analytical inference is provided by body parts detection, and is used to update subsets of state parameters representing the human pose. This reduces the degree of randomness and decreases the required number of particles. This new technique is a significant improvement over the standard particle filtering, with the advantages of performing automatic track initialization, recovering from tracking failures, and reducing the computational load.
AB - The paper introduces a framework that integrates analytical inference into the particle filtering scheme for human body tracking. The analytical inference is provided by body parts detection, and is used to update subsets of state parameters representing the human pose. This reduces the degree of randomness and decreases the required number of particles. This new technique is a significant improvement over the standard particle filtering, with the advantages of performing automatic track initialization, recovering from tracking failures, and reducing the computational load.
UR - http://www.scopus.com/inward/record.url?scp=84964374909&partnerID=8YFLogxK
U2 - 10.1109/MOTION.2002.1182229
DO - 10.1109/MOTION.2002.1182229
M3 - Conference contribution
AN - SCOPUS:84964374909
T3 - Proceedings - Workshop on Motion and Video Computing, MOTION 2002
SP - 159
EP - 165
BT - Proceedings - Workshop on Motion and Video Computing, MOTION 2002
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - Workshop on Motion and Video Computing, MOTION 2002
Y2 - 5 December 2002 through 6 December 2002
ER -