A Dynamic Reconfigurable Hardware/Software Architecture for Object Tracking in Video Streams

1. 1.

   Bissacco A, Meltzer J, Ghiasi S, Soatto S, Sarrafzadeh M: Fast visual feature selection and tracking in a hybrid reconfigurable architecture. UCLA, Los Angeles, Calif, USA; 2004.http://www.cs.ucla.edu/~bissacco/hybridfeatrack.html

   • Google Scholar
2. 2.

   Bobda C, Majer M, Ahmadinia A, et al.: The erlangen slot machine: a highly flexible fpga-based reconfigurable platform. Proceedings of the 13th Annual IEEE Symposium on Field-Programmable Custom Computing Machines (FCCM '05), April 2005, Napa, Calif, USA 319-320.

   • Google Scholar
3. 3.

   Chen J, Silver D, Parashar M: Real time feature extraction and tracking in a computational steering environment. In Proceedings of the High Performance Computing Symposium (HPC '03), March-April 2003, San Diego, Calif, USA. Society for Modeling and Simulation International; 155-160.

   • Google Scholar
4. 4.

   Feng X, Perona P: Real time motion detection system and scene segmentation. In Tech. Rep. CIT-CDS-98-004. California Institute of Technology, Pasadena, Calif, USA; 1998.

   • Google Scholar
5. 5.

   Ghiasi S, Nahapetian A, Moon HJ, Sarrafzadeh M: Reconfiguration in network of embedded systems: challenges and adaptive tracking case study. Journal of Embedded Computing 2005,1(1):147-166.

   • Google Scholar
6. 6.

   Kulaczewski MB, Siegel HJ: Implementations of a feature-based visual tracking algorithm on two MIMD machines. Proceedings of the International Conference on Parallel Processing, August 1997, Bloomington, Ill, USA 422-430.

   • Google Scholar
7. 7.

   Kulaczewski MB, Siegel HJ: SIMD and mixed-mode implementations of a visual tracking algorithm. Proceedings of the International Parallel Processing Symposium (IPPS/SPDP '98), March-April 1998, Orlando, Fla, USA 716-720.

   • Google Scholar
8. 8.

   Lucas BD, Kanade T: An iterative image registration technique with an application to stereo vision. Proceedings of the 7th International Joint Conference on Artificial Intelligence (IJCAI '81), August 1981, Vancouver, BC, Canada 674-679.

   • Google Scholar
9. 9.

   Lysaght P: FPGAs in the decade after the von Neumann century. Friday workshop at Design, Automation and Test European (DATE '06), March 2006, Munich, Germany

   • Google Scholar
10. 10.

    Nister D, Naroditsky O, Bergen J: Visual odometry. In Tech. Rep. CN5300. Sarnoff Corporation, Princeton, NJ, USA; 2004.

    • Google Scholar
11. 11.

    Shi J, Tomasi C: Good features to track. In Tech. Rep. TR-93-1399. Department of Computer Science, Cornell University, Ithaca, NY, USA; 1993.

    • Google Scholar
12. 12.

    Shi J, Tomasi C: Good features to track. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '94), June 1994, Seattle, Wash, USA 593-600.

    • Google Scholar
13. 13.

    Tomasi C, Kanade T: Detection and tracking of point features. In Tech. Rep. CMUCS-91-131. Carnegie Mellon University, Pittsburgh, Pa, USA; 1991.

    • Google Scholar
14. 14.

    Zinßer T, Gräßl C, Niemann H: Efficient feature tracking for long video sequences. Proceedings of the 26th DAGM Symposium, August-September 2004, Tübingen, Germany 326-333.

    • Google Scholar

Download references