Lab Meeting 22 Mar 2007 (Atwood): Fast, Integrated Person Tracking and Activity Recognition with Plan-View Templates from a Single Stereo Camera

Author:
Michael Harville, Hewlett-Packard Laboratories Center for Signal and Image Processing
Dalong Li, Georgia Inst. of Technology

Abstract:
Plan-view projection of real-time depth imagery can improve
the statistics of its intrinsic 3D data, and allows for
cleaner separation of occluding and closely-interacting people.
We build a probabilistic, real-time multi-person tracking
system upon a plan-view image substrate that well preserves
both shape and size information of foreground objects.
The tracking’s robustness derives in part from its “plan-view
template” person models, which capture detailed properties
of people’s body configurations. We demonstrate that these
same person models - obtained with a single compact stereo
camera unit - may also be used for fast recognition of body
pose and activity. Principal components analysis is used to
extract plan-view “eigenposes”, onto which person models,
extracted during tracking, are projected to produce a compact
representation of human body configuration. We then
formulate pose recognition as a classification problem, and
use support vector machines (SVMs) to quickly distinguish
between, for example, different directions people are facing,
and different body poses such as standing, sitting, bending
over, crouching, and reaching. The SVM outputs are transformed
to probabilities and integrated across time in a probabilistic
framework for real-time activity recognition.

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