Tracking and data association
Color-Based Probabilistic Tracking
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
State-space recursive least-squares: part I
Signal Processing - Special section: New trends and findings in antenna array processing for radar
Hardware/Software Co-Design of an FPGA-based Embedded Tracking System
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
ACM Computing Surveys (CSUR)
An Embedded Real-Time Surveillance System: Implementation and Evaluation
Journal of Signal Processing Systems
The estimation of the gradient of a density function, with applications in pattern recognition
IEEE Transactions on Information Theory
FPGA-based real-time optical-flow system
IEEE Transactions on Circuits and Systems for Video Technology
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The probabilistic visual tracking methods using color histograms have been proven to be robust to target model variations and background illumination changes as shown by the recent research. However, the required computational cost is high due to intensive image data processing. The embedded solution of such algorithms become challenging due to high computational power demand and algorithm complexity. This paper presents a hardware/software co-design architecture for implementation of the well-known kernel based mean shift tracking algorithm. The design uses color histogram of the target as tracking feature. The target is searched in the consecutive images by maximizing the statistical match of the color distributions. The target localization is based on gradient based iterative search instead of exhaustive search which makes the system capable of achieving frame rate up to hundreds of frames per second while tracking multiple targets. The design, which is fully standalone, is implemented on a low-cost medium-size field programmable gate array (FPGA) device. The hardware cost of the design is compared with some other tracking systems. The performance of the system in terms of speed is evaluated and compared with the software based implementation. It is expected that the proposed solution will find its utility in applications like embedded automatic video surveillance systems.