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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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
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