Object tracking on FPGA-based smart cameras using local oriented energy and phase features

Norouznezhad, Ehsan, Bigdeli, Abbas, Postula, Adam and Lovell, Brian C. (2010). Object tracking on FPGA-based smart cameras using local oriented energy and phase features. In: ICDSC '10 Proceedings of the Fourth ACM/IEEE International Conference on Distributed Smart Cameras. International Conference on Distributed Smart Cameras (ICDSC 2010), Atlanta, GA, United States, (33-40). 31 August - 4 September 2010. doi:10.1145/1865987.1865993

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Author Norouznezhad, Ehsan
Bigdeli, Abbas
Postula, Adam
Lovell, Brian C.
Title of paper Object tracking on FPGA-based smart cameras using local oriented energy and phase features
Conference name International Conference on Distributed Smart Cameras (ICDSC 2010)
Conference location Atlanta, GA, United States
Conference dates 31 August - 4 September 2010
Proceedings title ICDSC '10 Proceedings of the Fourth ACM/IEEE International Conference on Distributed Smart Cameras
Journal name ICDSC - 4th ACM/IEEE International Conference on Distributed Smart Cameras
Place of Publication New York, United States
Publisher ACM
Publication Year 2010
Sub-type Fully published paper
DOI 10.1145/1865987.1865993
Open Access Status File (Author Post-print)
ISBN 9781450303170
Start page 33
End page 40
Total pages 8
Language eng
Abstract/Summary This paper presents the use of local oriented energy and phase features for real-time object tracking on smart cameras. In our proposed system, local energy features are used as spatial feature set for representing the target region while the local phase information are used for estimating the motion pattern of the target region. The motion pattern information of the target region is used for displacement of search area. Local energy and phase features are extracted by filtering the incoming images with a bank of complex Gabor filters. The effectiveness of the chosen feature set is tested using a mean-shift tracker. Our experiments show that the proposed system can significantly enhance the performance of the tracker in presence of photometric variations and geometric transformation. The real-time implementation of the system is also described in this paper. To achieve the desired performance, a hardware/software co-design approach is pursued. Apart from mean-shift vector calculation, the other blocks are implemented on hardware resources. The system was synthesized onto a Xilinx Virtex-5 XC5VSX50T using Xilinx ML506 development board and the implementation results are presented.
Keyword Object tracking
Smart camera
Gabor filters
Mean-shift tracking
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status UQ

 
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Created: Thu, 10 Mar 2011, 15:53:27 EST by Mr Ehsan Norouznezhad on behalf of School of Information Technol and Elec Engineering