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The Multi-strand Graph for a PTZ Tracker

NCJ Number
253332
Date Published
2018
Length
15 pages
Author(s)
Shachaf Melman; Yael Moses; Cerard Medioni; Yinghao Cai
Agencies
NIJ-Sponsored
Publication Type
Research (Applied/Empirical), Report (Study/Research), Report (Grant Sponsored), Program/Project Description
Grant Number(s)
2011-IJ-CX-K054
Annotation
Since a central component of a PTZ tracking system is a scheduling algorithm that determines which target to zoom in on, particularly when the high-resolution images are also used for tracklet matching, the current study examined this scheduling problem from a theoretical perspective, proposing a novel data structure, the Multi-strand Tracking Graph (MSG), which represents the set of tracklets computed by a tracker and the possible associations between them.
Abstract
High-resolution images can be used to resolve matching ambiguities between trajectory fragments (tracklets), which is a key challenge in multiple-target tracking. A pan-tilt-zoom (PTZ) camera, which can pan, tilt and zoom, is a powerful and efficient tool that offers both close-up views and wide area coverage on demand. The wide area enables tracking of many targets, while the close-up view allows individuals to be identified from high-resolution images of their faces. The current project determined that the MSG allows efficient scheduling, as well as resolving of matching ambiguities between tracklets. The main feature of the MSG is the auxiliary data saved in each vertex, which allows efficient computation while avoiding time-consuming graph traversal. Synthetic data simulations were used to evaluate the scheduling algorithm and to demonstrate its superiority over a naïve one. (publisher abstract modified)
Date Created: July 20, 2021