A neuro-inspired visual tracking method based on programmable system-on-chip platform

Using programmable system-on-chip to implement computer vision functions poses many challenges due to highly constrained resources in cost, size and power consumption. In this work, we propose a new neuro-inspired image processing model and implemented it on a system-on-chip Xilinx Z702c board. With...

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Bibliographic Details
Published in:Neural computing & applications 2018-11, Vol.30 (9), p.2697-2708
Main Authors: Yang, Shufan, Wong-Lin, KongFatt, Andrew, James, Mak, Terrence, McGinnity, T. Martin
Format: Article
Language:English
Subjects:
Artificial Intelligence
Computational Biology/Bioinformatics
Computational Science and Engineering
Computer Science
Computer vision
Data Mining and Knowledge Discovery
Frames per second
Image processing
Image Processing and Computer Vision
Iterative methods
Neural networks
Occlusion
Optical tracking
Original Article
Power consumption
Probability and Statistics in Computer Science
System on chip
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Summary:Using programmable system-on-chip to implement computer vision functions poses many challenges due to highly constrained resources in cost, size and power consumption. In this work, we propose a new neuro-inspired image processing model and implemented it on a system-on-chip Xilinx Z702c board. With the attractor neural network model to store the object’s contour information, we eliminate the computationally expensive steps in the curve evolution re-initialisation at every new iteration or frame. Our experimental results demonstrate that this integrated approach achieves accurate and robust object tracking, when they are partially or completely occluded in the scenes. Importantly, the system is able to process 640 by 480 videos in real-time stream with 30 frames per second using only one low-power Xilinx Zynq-7000 system-on-chip platform. This proof-of-concept work has demonstrated the advantage of incorporating neuro-inspired features in solving image processing problems during occlusion.
ISSN:0941-0643
1433-3058
DOI:10.1007/s00521-017-2847-5