Robust Tracking Occluded Human in Group by Perception Sensors Network System

Title
Robust Tracking Occluded Human in Group by Perception Sensors Network System
Authors
최종석Anh Vu Le
Keywords
sensor fusion; Sensors network; human detection; Group tracking; human tracking; Features matching
Issue Date
2018-06
Publisher
Journal of intelligent & robotic systems
Citation
VOL 90, NO 3-4-361
Abstract
Tracking people even being partially or fully occluded in the group situation is studied using a Perception Sensor Network (PSN) system which is composed of multiple Kinects used to detect human 3D locations, and pan tilt zoom (PTZ) cameras used to identify human faces. A method is proposed to fuse multiple detection of human in the PSN system. After associating detected human with corresponding names, the novel grouping and ungrouping algorithms are proposed. When a group of multiple human staying close together is formed, viewpoint and illumination invariant features of group members including human 3D location, height, color and binary robust invariant scalable keypoint (BRISK), retrieved from region of interest (ROI) of both depth and color images, are then stored and updated into the group database. Based on the distance between a group location at previous frame and each member location in the group at current frame, the PSN system decides whether to keep the members in the group or to ungroup them then reassign the right name among the group database by minimizing multiple criterions. The experimental results demonstrate the outperforming of the proposed method on tracking people in group than conventional methods.
URI
http://pubs.kist.re.kr/handle/201004/66671
ISSN
0921-0296
Appears in Collections:
KIST Publication > Article
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