High-Speed Target Tracking System Based on a Hierarchical Parallel Vision Processor and Gray-Level LBP Algorithm

• Published in: IEEE transactions on systems, man, and cybernetics. Systems Vol. 47; no. 6; pp. 950 - 964
• Main Authors: Yang, Yongxing, Yang, Jie, Liu, Liyuan, Wu, Nanjian
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.06.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Actuators; AdaBoost; Algorithms; Arrays; CMOS; Digital cameras; gray-level local binary pattern (GLLBP); hierarchical; High speed; Image processing; Image resolution; Levels; Luminance distribution; Microprocessors; Parallel processing; Product development; Registers; Robustness; Target tracking; Tracking systems; Vision; vision processor
• ISSN: 2168-2216; 2168-2232
• DOI: 10.1109/TSMC.2016.2523907

Visual target tracking has made significant advances in past decades. However, fast and robust vision target tracking systems are still greatly demanded. This paper proposes a novel high-speed target tracking system based on hierarchical parallel vision processor architecture. This system contains three main parts: 1) a CMOS image sensor; 2) a vision processor; and 3) an actuator with two degrees of freedom. The vision processor integrates a pixel-parallel processing element (PE) array, a row-parallel row processor (RP) array, dual-core microprocessor unit (MPU) and motor controller. The PE array and RP array can speed up low-level and middle-level image processing operations by O(M 2 ) and O(M), respectively. The MPU is responsible for the high-level image processing and the overall chip management. A novel tracking algorithm based on a gray-level local binary pattern descriptor is proposed. The descriptor describes not only local texture feature but also distribution of luminance. The algorithm increases the robustness of the tracking system under low resolution scenery and complex background. It can be carried out by the vision processor with very high efficiency. Experiment results demonstrate that the system can track a fast moving target under complex conditions and the vision processor can achieve over 2000 frames/s processing speed of the target tracking algorithm with 750×480 image resolution.