What is it about?
In recent years, automated human tracking over camera networks is getting essential for video surveillance. The tasks of tracking human over camera networks are not only inherently challenging due to changing human appearance, but also have enormous potentials for a wide range of practical applications, ranging from security surveillance to retail and healthcare.
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Why is it important?
This review paper surveys the most widely used techniques and recent advances for human tracking over camera networks. Two important functional modules for the human tracking over camera networks are addressed, including human tracking within a camera and human tracking across non overlapping cameras. The core techniques of human tracking within a camera are discussed based on two aspects, i.e., generative trackers and discriminating trackers. The core techniques of human tracking across non-overlapping cameras are then discussed based on the aspects of human re-identification, camera-link model-based tracking, and graph model-based tracking.
Perspectives
Our survey aims to address existing problems, challenges, and future research directions based on the analyses of the current progress made toward human tracking techniques over camera networks.
Dr. Muhammad Rizwan
Shanghai University
Read the Original
This page is a summary of: Human detection and tracking over camera networks: A review, July 2016, Institute of Electrical & Electronics Engineers (IEEE),
DOI: 10.1109/icalip.2016.7846643.
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