NDLI: Human motion recognition based on statistical shape analysis

Content Provider	IEEE Xplore Digital Library
Author	Ning Jin Mokhtarian, F.
Copyright Year	2005
Description	Author affiliation: Centre for Vision, Speech, & Signal Process., Surrey Univ., Guildford, UK (Ning Jin; Mokhtarian, F.)
Abstract	Dynamic shape is a time series of the outlines of a moving object, which records the temporal variation of the shape of the object during its movement. We believe that the dynamic shape provides clues about the motion performed by the object. In this paper, we borrow tools from system identification to capture the "essence" of the dynamic shape, so that we convert the problems of modelling, learning, and recognizing object motions to the modelling, learning, and comparing of dynamical systems where each motion is represented. Concretely, we use Kenall's definition of shape to represent object contours extracted from each frame, and construct a tangent space with the full Procrustes mean shape as the pole to approximate a linear space for the data set; we then apply these linearized contour representations as training data to learn the dynamical systems, i.e. estimate system parameters; finally supervised pattern classification techniques based on various types of distance measure are adopted for recognition.
Starting Page	4
Ending Page	9
File Size	678491
Page Count	6
File Format	PDF
ISBN	0780393856
DOI	10.1109/AVSS.2005.1577234
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-09-15
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Parameter estimation Shape measurement Humans Linear approximation Training data Pattern classification System identification Pattern recognition Data mining Motion analysis
Content Type	Text
Resource Type	Article

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