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 am 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 recognition method comprising:
determining, by a controller, principal components of depth images and binary shape images of human activities extracted from a video clip; performing, by the controller, a human activity modeling based on the principal components; and determining, by the controller, a human activity model which maximizes a likelihood probability among activity models in a dictionary according to an output value of the human activity modeling, wherein the depth images of the human activities are different images than the binary shape images of the human activities, and the video clip comprises successive images that are based on a video sensor.