Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
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While the 3D-TV becomes widely available in the market, consumers will face the problem of serious shortage of 3D video content. Since the difficulty of 3D video capturing and manufacturing, the automatic video conversion from 2D serves as an important solution for producing 3D perception. However, 2D-to-3D video conversion is a compute-intensive task and real-time processing speed is required in online playing. Nowadays, with the multi-core processor becoming the mainstream, 2D-to-3D video conversion can be accelerated by fully utilizing the computing power of available multi-core processors. In this paper, we take a typical algorithm of automatic 2D-to-3D video conversion as reference and present typical optimization techniques to improve the implementation performance. The result shows our optimization can do the conversion on an average of 36 frames per second on an Intel Core i7 2.3 GHz processor, which meets the real-time processing requirement. We also conduct a scalability performance analysis on the multi-core system to identify the causes of bottlenecks, and make suggestion for optimization of this workload on large-scale multi-core systems.