Apparatus and method for video sensor-based human activity and facial expression modeling and recognition

摘要

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.

主权项

1. A human activity modeling method comprising:
determining, by a controller, principal components of depth images and binary shape images of human activities extracted from video clips, wherein the depth images of the human activities are different images than the binary shape images of the human activities; determining, by the controller, Independent Component Analysis (ICA) representations based on the principal components; determining, by the controller, features through Linear Discriminant Analysis (LDA) based on the ICA representations; determining, by the controller, a codebook using vector quantization; determining, by the controller, observation symbol sequences in the video clips; and identifying, by the controller, human activities using a Hidden Markov Model (HMM) based on a status transition and an observation matrix.