Abstract
Accurate object recognition based on image processing is required in embedded applications, where real-time processing is expected to incorporate accurate recognition. To achieve accurate real-time object recognition, an accurate recognition algorithm that can be quickened by parallel implementation and a processing system that can execute such algorithms in real-time are necessary. In this paper, we implemented an accurate recognition scheme in parallel that consists of boosting-based detection and histogram-based tracking on a Cell Broadband Engine (Cell), one of the latest high performance embedded processors. We show that the Cell can achieve real-time object recognition on QVGA video at 22 fps with three targets and 18 fps with eight targets . Furthermore, we constructed a real-time object recognition system using SONY® Playstation 3, one of the most widely used Cell platforms, and demonstrated face recognition with it.
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Sugano, H., Miyamoto, R. (2007). A Real-Time Object Recognition System on Cell Broadband Engine. In: Mery, D., Rueda, L. (eds) Advances in Image and Video Technology. PSIVT 2007. Lecture Notes in Computer Science, vol 4872. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77129-6_78
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DOI: https://doi.org/10.1007/978-3-540-77129-6_78
Publisher Name: Springer, Berlin, Heidelberg
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