TY - GEN
T1 - Recognizing human actions based on silhouette energy image and global motion description
AU - Ahmad, Mohiuddin
AU - Lee, Seong Whan
PY - 2008
Y1 - 2008
N2 - In this paper, we propose a spatio-temporal silhouette, called silhouette energy image (SEI), and models, to characterize motion and shape properties automatic recognition of human actions in daily . To address the variability in the recognition of human, several parameters, such as anthropometry of the, speed of the action, phase (starting and ending state an action), camera observations (distance from camera, motion, and rotation of human body), and view are proposed. We construct the variability models on SEI and the variability parameters. The global based motions express the spatio-temporal properties SEI and variability models. Our construction of the model for each action and view is based on the vectors of motion descriptions of combined action . We recognize different daily human actions of different successfully in the indoor and outdoor environment. experimental results show that the proposed of human action recognition is robust, flexible and efficient.
AB - In this paper, we propose a spatio-temporal silhouette, called silhouette energy image (SEI), and models, to characterize motion and shape properties automatic recognition of human actions in daily . To address the variability in the recognition of human, several parameters, such as anthropometry of the, speed of the action, phase (starting and ending state an action), camera observations (distance from camera, motion, and rotation of human body), and view are proposed. We construct the variability models on SEI and the variability parameters. The global based motions express the spatio-temporal properties SEI and variability models. Our construction of the model for each action and view is based on the vectors of motion descriptions of combined action . We recognize different daily human actions of different successfully in the indoor and outdoor environment. experimental results show that the proposed of human action recognition is robust, flexible and efficient.
UR - http://www.scopus.com/inward/record.url?scp=67650697294&partnerID=8YFLogxK
U2 - 10.1109/AFGR.2008.4813435
DO - 10.1109/AFGR.2008.4813435
M3 - Conference contribution
AN - SCOPUS:67650697294
SN - 9781424421541
T3 - 2008 8th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2008
BT - 2008 8th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2008
T2 - 2008 8th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2008
Y2 - 17 September 2008 through 19 September 2008
ER -