Abstract: An apparatus and method for human activity and facial expression modeling and recognition are based on feature extraction techniques from time sequential images. The human activity modeling includes determining principal components of depth and/or binary shape images of human activities extracted from video clips. Independent Component Analysis (ICA) representations are determined based on the principal components. Features are determined through Linear Discriminant Analysis (LDA) based on the ICA representations. A codebook is determined using vector quantization. Observation symbol sequences in the video clips are determined. And human activities are learned using the Hidden Markov Model (HMM) based on status transition and an observation matrix.
Type:
Grant
Filed:
June 4, 2010
Date of Patent:
June 17, 2014
Assignees:
Samsung Electronics Co., Ltd., Kyung Hee University, University-Industry Cooperation Group of Kyung Hee University
Inventors:
Hyun-Soo Kim, Jong-Chang Lee, Dae-Hyun Sim, Tae-Seong Kim