Accelerating object detection via a visual-feature-directed search cascade: algorithm and field programmable gate array implementation

Christos Kyrkou; Theocharis Theocharides

doi:10.1117/1.JEI.25.4.041013

3 August 2016 Accelerating object detection via a visual-feature-directed search cascade: algorithm and field programmable gate array implementation

Christos Kyrkou, Theocharis Theocharides

Author Affiliations +

Journal of Electronic Imaging, Vol. 25, Issue 4, 041013 (August 2016). https://doi.org/10.1117/1.JEI.25.4.041013

Abstract

Object detection is a major step in several computer vision applications and a requirement for most smart camera systems. Recent advances in hardware acceleration for real-time object detection feature extensive use of reconfigurable hardware [field programmable gate arrays (FPGAs)], and relevant research has produced quite fascinating results, in both the accuracy of the detection algorithms as well as the performance in terms of frames per second (fps) for use in embedded smart camera systems. Detecting objects in images, however, is a daunting task and often involves hardware-inefficient steps, both in terms of the datapath design and in terms of input/output and memory access patterns. We present how a visual-feature-directed search cascade composed of motion detection, depth computation, and edge detection, can have a significant impact in reducing the data that needs to be examined by the classification engine for the presence of an object of interest. Experimental results on a Spartan 6 FPGA platform for face detection indicate data search reduction of up to 95%, which results in the system being able to process up to 50 1024×768 pixels images per second with a significantly reduced number of false positives.

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Christos Kyrkou and Theocharis Theocharides "Accelerating object detection via a visual-feature-directed search cascade: algorithm and field programmable gate array implementation," Journal of Electronic Imaging 25(4), 041013 (3 August 2016). https://doi.org/10.1117/1.JEI.25.4.041013

Published: 3 August 2016

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