báo cáo hóa học:" Research Article Cascade Boosting-Based Object Detection from High-Level Description to Hardware Implementation"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Cascade Boosting-Based Object Detection from High-Level Description to Hardware Implementation | Hindawi Publishing Corporation EURASIP Journal on Embedded Systems Volume 2009 Article ID 235032 12 pages doi 2009 235032 Research Article Cascade Boosting-Based Object Detection from High-Level Description to Hardware Implementation K. Khattab J. Dubois and J. Miteran Le2i UMR CNRS 5158 Aile des Sciences de ringenieur Universite de Bourgogne BP 47870 21078 Dijon Cedex France Correspondence should be addressed to J. Dubois jdubois@ Received 28 February 2009 Accepted 30 June 2009 Recommended by Bertrand Granado Object detection forms the first step of a larger setup for a wide variety of computer vision applications. The focus of this paper is the implementation of a real-time embedded object detection system while relying on high-level description language such as SystemC. Boosting-based object detection algorithms are considered as the fastest accurate object detection algorithms today. However the implementation of a real time solution for such algorithms is still a challenge. A new parallel implementation which exploits the parallelism and the pipelining in these algorithms is proposed. We show that using a SystemC description model paired with a mainstream automatic synthesis tool can lead to an efficient embedded implementation. We also display some of the tradeoffs and considerations for this implementation to be effective. This implementation proves capable of achieving 42 fps for 320 X 240 images as well as bringing regularity in time consuming. Copyright 2009 K. Khattab et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 1. Introduction Object detection is the task of locating an object in an image despite considerable variations in lighting background and object appearance. The ability of object detecting in a scene is critical in our everyday life activities and lately

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