Authors:
Alvaro Fernandez-Rincon
;
David Fuentes-Jimenez
;
Cristina Losada-Gutierrez
;
Marta Marron-Romera
;
Carlos A. Luna
;
Javier Macias-Guarasa
and
Manuel Mazo
Affiliation:
University of Alcalá, Spain
Keyword(s):
People Detection, Tracking, Time-of-Flight, ToF Camera.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Image and Video Analysis
;
Motion, Tracking and Stereo Vision
;
Segmentation and Grouping
;
Video Surveillance and Event Detection
Abstract:
In this paper we describe a system for robust detection of people in a scene, by using an overhead Time of
Flight (ToF) camera. The proposal addresses the problem of robust detection of people, by three means: a
carefully designed algorithm to select regions of interest as candidates to belong to people; the generation
of a robust feature vector that efficiently model the human upper body; and a people classification stage, to
allow robust discrimination of people and other objects in the scene. The proposal also includes a particle
filter tracker to allow people identification and tracking. Two classifiers are evaluated, based on Principal
Component Analysis (PCA), and Support Vector Machines (SVM). The evaluation is carried out on a subset
of a carefully designed dataset with a broad variety of conditions, providing results comparing the PCA and
SVM approaches, and also the performance impact of the tracker, with satisfactory results.