Abstract
The rapid increase in pixel density and frame rates of modern imaging sensors is accelerating the demand for fine-grained and embedded parallelization strategies to achieve real-time implementations for video analysis. The IBM Cell Broadband Engine (BE) processor has an appealing multi-core chip architecture with multiple programming models suitable for accelerating multimedia and vector processing applications. This paper describes two parallel algorithms for blob extraction in video sequences: binary morphological operations and connected components labeling (CCL), both optimized for the Cell-BE processor. Novel parallelization and explicit instruction level optimization techniques are described for fully exploiting the computational capacity of the Synergistic Processing Elements (SPEs) on the Cell processor. Experimental results show significant speedups ranging from a factor of nearly 300 for binary morphology to a factor of 8 for CCL in comparison to equivalent sequential implementations applied to High Definition (HD) video.
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References
Bunyak, F., Palaniappan, K., Nath, S., Seetharaman, G.: Flux tensor constrained geodesic active contours with sensor fusion for persistent object tracking. J. Multimedia 2(4), 20–33 (2007)
Bunyak, F., Palaniappan, K., Nath, S.K., Baskin, T.I., Dong, G.: Quantitative cell motility for in vitro wound healing using level set-based active contour tracking. In: Proc. 3rd IEEE Int. Symp. Biomed. Imaging (ISBI), April 2006, pp. 1040–1043 (2006)
Bunyak, F., Palaniappan, K., Nath, S.K., Seetharaman, G.: Geodesic active contour based fusion of visible and infrared video for persistent object tracking. In: IEEE Workshop Applications of Computer Vision (WACV 2007), page Online (2007)
Buttari, A., Luszczek, P., Kurzak, J., Dongarra, J., Bosilca, G.: A rough guide to scientific computing on the Playstation 3. Technical Report UT-CS-07-595, Innovative Computing Laboratory, University of Tennessee Knoxville (2007)
Chen, T.P., Budnikov, D., Hughes, C.J., Chen, Y.-K.: Computer vision on multi-core processors: Articulated body tracking. In: IEEE Int. Conf. Multimedia and Expo., pp. 1862–1865 (2007)
Fatahalian, K., Knight, T.J., Houston, M., Erez, M., Horn, D.R., Leem, L., Park, J.-Y., Ren, M., Aiken, A., Dally, W.J., Hanrahan, P.: Sequoia: Programming the memory hierarchy. In: Proc. ACM/IEEE Conf. Supercomputing (2006)
Hidemasa, M., Munehiro, D., Hiroki, N., Yumi, M.: Multilevel parallelization on the Cell/B.E. for a motion JPEG 2000 encoding server. In: Proc. 15th Int. Conf. Multimedia, pp. 942–951 (2007)
Kolekar, M.H., Palaniappan, K., Sengupta, S., Seetharaman, G.: Semantic concept mining based on hierarchical event detection for soccer video indexing. J. Multimedia (2009)
Liu, L., Kesavarapu, S., Connell, J., Jagmohan, A., Leem, A., Paulovicks, L., Sheinin, B., Tang, V.L., Yeo, H.: Video analysis and compression on the STI Cell Broadband Engine processor. In: IEEE Int. Conf. Multimedia and Expo. (2006)
Manohar, M., Ramapriyan, H.K.: Connected component labeling of binary images on a mesh connected massively parallel processor. Computer Vision, Graphics, and Image Processing 45(2), 133–149 (1989)
Momcilovic, S., Sousa, L.: A parallel algorithm for advanced video motion estimation on multicore architectures. In: Int. Conf. Complex, Intelligent and Software Intensive Systems, pp. 831–836 (2008)
Palaniappan, K., Kumar, P., Ersoy, I., Davis, S.R., Bunyak, F., Linderman, M., Seetharaman, G., Linderman, R.: Parallel flux tensor for real-time moving object detection. Submitted to International Conference on Image Processing (2009)
Shyu, C.R., Klaric, M., Scott, G., Barb, A., Davis, C., Palaniappan, K.: GeoIRIS: Geospatial information retrieval and indexing system – content mining, semantics, modeling, and complex queries. IEEE Trans. Geoscience and Remote Sensing 45(4), 839–852 (2007)
Sugano, H., Miyamoto, R.: Parallel implementation of morphological processing on cell/be with opencv interface. In: 3rd Int. Symp. Communications, Control and Signal Processing, pp. 578–583 (2008)
Williams, S., Shalf, J., Oliker, L., Kamil, S., Husbands, P., Yelick, K.: Scientific computing kernels on the Cell processor. Int. J. Parallel Progrm. 35, 263–298 (2007)
Yu, J., Wei, H.: Video processing and retrieval on cell processor architecture. In: Ma, L., Rauterberg, M., Nakatsu, R. (eds.) ICEC 2007. LNCS, vol. 4740, pp. 255–262. Springer, Heidelberg (2007)
Zhou, L., Kambhamettu, C., Goldgof, D., Palaniappan, K., Hasler, A.F.: Tracking non-rigid motion and structure from 2D satellite cloud images without correspondences. IEEE Trans. Pattern Analysis and Machine Intelligence 23(11), 1330–1336 (2001)
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Kumar, P., Palaniappan, K., Mittal, A., Seetharaman, G. (2009). Parallel Blob Extraction Using the Multi-core Cell Processor. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2009. Lecture Notes in Computer Science, vol 5807. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04697-1_30
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DOI: https://doi.org/10.1007/978-3-642-04697-1_30
Publisher Name: Springer, Berlin, Heidelberg
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