TY - GEN
T1 - Motion estimation of deformable target over infrared camera video in coarse resolution with possible frame-out of target by particle filter
AU - Ikoma, Norikazu
AU - Koshiba, Mamiko
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/9/8
Y1 - 2015/9/8
N2 - Motion estimation of deformable target over infrared camera video in coarse resolution with possible frame-out of the target by an elaborated particle filter has been proposed. Target state consists of location factor and shape factor of the target, where the location factor is position of the center of gravity of the target over the image plane, and the shape factor is a set of connected pixels that forms appearance of the target over the image plane. The location factor is formulated in real number space, while the shape factor is formulated in pixel based manner. State space model has been formed by a system model to represent a smooth motion of the target and smooth change of its shape, and by an observation model to evaluated likeliness of the state based on an appearance of the target over the image plane. We have employed a mixture model for the location factor of the system model consisting of second order difference equation for smooth change and uniform distribution over the image plane to cope with abrupt change of the location due to lack of frame rate in the video. For the smooth change of the target shape, we propose to use a Markov Chain Monte Carlo move on the set of connected pixels. Experiments on some real video images explore the performance of the proposed method through a prototyped implementation by simplifying the method with rough approximation of the target shape with a rectangle.
AB - Motion estimation of deformable target over infrared camera video in coarse resolution with possible frame-out of the target by an elaborated particle filter has been proposed. Target state consists of location factor and shape factor of the target, where the location factor is position of the center of gravity of the target over the image plane, and the shape factor is a set of connected pixels that forms appearance of the target over the image plane. The location factor is formulated in real number space, while the shape factor is formulated in pixel based manner. State space model has been formed by a system model to represent a smooth motion of the target and smooth change of its shape, and by an observation model to evaluated likeliness of the state based on an appearance of the target over the image plane. We have employed a mixture model for the location factor of the system model consisting of second order difference equation for smooth change and uniform distribution over the image plane to cope with abrupt change of the location due to lack of frame rate in the video. For the smooth change of the target shape, we propose to use a Markov Chain Monte Carlo move on the set of connected pixels. Experiments on some real video images explore the performance of the proposed method through a prototyped implementation by simplifying the method with rough approximation of the target shape with a rectangle.
KW - deformable object
KW - particle filter
KW - visual tracking
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U2 - 10.1109/ASCC.2015.7244777
DO - 10.1109/ASCC.2015.7244777
M3 - Conference contribution
AN - SCOPUS:84957670727
T3 - 2015 10th Asian Control Conference: Emerging Control Techniques for a Sustainable World, ASCC 2015
BT - 2015 10th Asian Control Conference
A2 - Selamat, Hazlina
A2 - Ramli, Hafiz Rashidi Haruna
A2 - Faudzi, Ahmad Athif Mohd
A2 - Rahman, Ribhan Zafira Abdul
A2 - Ishak, Asnor Juraiza
A2 - Soh, Azura Che
A2 - Ahmad, Siti Anom
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th Asian Control Conference, ASCC 2015
Y2 - 31 May 2015 through 3 June 2015
ER -