FPGA implementation of an embedded face detection system based on LEON3

This paper presents an FPGA face detection embedded system. In order achieve acceleration in the face detection process a hardware-software codesign technique is proposed. The paper describes the face detection acceleration mechanism. It also describes the implementation of an IP module that allows hardware acceleration.Comisión Europea MOBY-DIC FP7-IST-248858Ministerio de Ciencia y Tecnología TEC2011-24319Junta de Andalucía P08-TIC-0367

Design Methodology for Face Detection Acceleration

A design methodology to accelerate the face detection for embedded systems is described, starting from high level (algorithm optimization) and ending with low level (software and hardware codesign) by addressing the issues and the design decisions made at each level based on the performance measurements and system limitations. The implemented embedded face detection system consumes very little power compared with the traditional PC software implementations while maintaining the same detection accuracy. The proposed face detection acceleration methodology is suitable for real time applications.Ministerio español de Ciencia y Tecnología TEC2011-24319Junta de Andalucía FEDER P08-TIC-0367

RASW: A run-time adaptive sliding window to improve Viola-Jones object detection

Abstract—In recent years accurate algorithms for detecting objects in images have been developed. Among these algorithms, the object detection scheme proposed by Viola and Jones gained great popularity, especially after the release of high-quality face classifiers by the OpenCV group. However, as any other slidingwindow based object detector, it is affected by a strong increase in the computational cost as the size of the scene grows. Especially in real-time applications, a search strategy based on a sliding window can be computationally too expensive. In this paper, we propose an efficient approach to adapt at run time the sliding window step size in order to speed-up the detection task without compromising the accuracy. We demonstrate the effectiveness of the proposed Run-time Adaptive Sliding Window (RASW) in improving the performance of Viola-Jones object detection by providing better throughput-accuracy tradeoffs. When comparing our approach with the OpenCV face detection implementation, we obtain up to 2.03x speedup in frames per second without any loss in accuracy

Accelerating Viola-Jones face detection for embedded and SoC environments

In this communication a speed optimized implementation of Viola-Jones Face Detection Algorithm based on the baseline OpenCV face detection application is presented. The baseline OpenCV face detection application is analyzed. Then the necessary modifications and improvements are described in order to accelerate the execution speed in an embedded or SoC (System-on-Chip) environments.Peer Reviewe