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Embedded Vision Insights: August 2, 2016 Edition

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Combining Flexibility and Low-Power in Embedded Vision Subsystems: An Application to Pedestrian DetectionSynopsys
Bruno Lavigueur, Embedded Vision Subsystem Project Leader at Synopsys, presents a case study of a pedestrian detection application. Starting from a high-level functional description in OpenCV, he decomposes and maps the application onto a heterogeneous platform consisting of a high-performance control processor and ASIPS (application-specific instruction-set processors). This application makes use of the HOG (Histogram of Oriented Gradients) algorithm. Lavigueur reviews the computation requirements of the different algorithm kernels, and presents possible mapping options onto the control processor and ASIPs. He also presents an OpenCV-to-ASIP software refinement methodology and supporting tools. He presents detailed results of the final configuration, consisting of one control processor and four ASIPs, including cost and power figures. Finally, he summarizes the results on an FPGA-based rapid prototyping platform.

Real-Time Traffic Sign Recognition on Mobile ProcessorsNVIDIA
There is a growing need for fast and power-efficient computer vision on embedded devices. This session from NVIDIA's GTC (GPU Technology Conference) focuses on computer...