Illumination-robust people tracking using a smart camera network

Nyan Bo Bo; Peter Van Hese; Junzhi Guan; Sebastian Gruenwedel; Jorge Niño-Castañeda; Dimitri Van Cauwelaert; Dirk Van Haerenborgh; Peter Veelaert; Wilfried Philips

doi:10.1117/12.2036764

3 February 2014 Illumination-robust people tracking using a smart camera network

Nyan Bo Bo, Peter Van Hese, Junzhi Guan, Sebastian Gruenwedel, Jorge Niño-Castañeda, Dimitri Van Cauwelaert, Dirk Van Haerenborgh, Peter Veelaert, Wilfried Philips

Author Affiliations +

Proceedings Volume 9025, Intelligent Robots and Computer Vision XXXI: Algorithms and Techniques; 90250G (2014) https://doi.org/10.1117/12.2036764
Event: IS&T/SPIE Electronic Imaging, 2014, San Francisco, California, United States

Abstract

Many computer vision based applications require reliable tracking of multiple people under unpredictable lighting conditions. Many existing trackers do not handle illumination changes well, especially sudden changes in illumination. This paper presents a system to track multiple people reliably even under rapid illumination changes using a network of calibrated smart cameras with overlapping views. Each smart camera extracts foreground features by detecting texture changes between the current image and a static background image. The foreground features belonging to each person are tracked locally on each camera but these local estimates are sent to a fusion center which combines them to generate more accurate estimates. The nal estimates are fed back to all smart cameras, which use them as prior information for tracking in the next frame. The texture based approach makes our method very robust to illumination changes. We tested the performance of our system on six video sequences, some containing sudden illumination changes and up to four walking persons. The results show that our tracker can track multiple people accurately with an average tracking error as low as 8 cm even when the illumination varies rapidly. Performance comparison to a state-of-the-art tracking system shows that our method outperforms.

Citation Download Citation

Nyan Bo Bo, Peter Van Hese, Junzhi Guan, Sebastian Gruenwedel, Jorge Niño-Castañeda, Dimitri Van Cauwelaert, Dirk Van Haerenborgh, Peter Veelaert, and Wilfried Philips "Illumination-robust people tracking using a smart camera network", Proc. SPIE 9025, Intelligent Robots and Computer Vision XXXI: Algorithms and Techniques, 90250G (3 February 2014); https://doi.org/10.1117/12.2036764

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
10 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Cameras

Video

Image fusion

Light sources and illumination

Imaging systems

Data fusion

Calibration

Show All Keywords

Keywords/Phrases

Search In:

Publication Years