Algorithm Of Face Detection Research Articles

A parallel algorithm of multiple face detection on multi-core system

<p><span lang="EN-US">This work offers a graphics processing unit (GPU)-based system for real-time face recognition, which can detect and identify faces with high accuracy. This work created and implemented novel parallel strategies for image integral, computation scan window processing, and classifier amplification and correction as part of the face identification phase of the Viola-Jones cascade classifier. Also, the algorithm and parallelized a portion of the testing step during the facial recognition stage were experimented with. The suggested approach significantly improves existing facial recognition methods by enhancing the performance of two crucial components. The experimental findings show that the proposed method, when implemented on an NVidia GTX 570 graphics card, outperforms the typical CPU program by a factor of 19.72 in the detection phase and 1573 in the recognition phase, with only 2000 images trained and 40 images tested. The recognition rate will plateau when the hardware's capabilities are maxed out. This demonstrates that the suggested method works well in real-time.</span></p>

Improved Viola-Jones face detection algorithm based on HoloLens

The current face detection in Microsoft HoloLens can only be achieved by remote call of face detection interface algorithm which is, however, restricted by network, resulting in slow detection and failing to meet real-time detection demand. This paper proposes an improved Viola-Jones algorithm of face detection based on HoloLens upgrading classical Viola-Jones face detection algorithm relying on Haar-like rectangle feature expansion to enhance detection efficiency, and accelerating detection building on two-dimensional convolution separation and image re-sampling technique. The detection efficiency of improved face detection algorithm is 12% on average higher than that of existing face detection interface algorithm, and its detection speed is four-folded. Moreover, HoloLens depth camera enables 3D face detection and location, and its unique gaze, voice, and gesture interacting techniques free the hands, thereby realizing easier and less-burdened man-computer interaction. HoloLens furnished with real-time video face detection algorithm as detailed in this paper can be applied in such fields as social contact, public security, and business management.

Face Detection System Based on SIFT Algorithm

This paper consists of three chapters, first introduced the algorithm and methods of Face detection, and then focus on the SIFT algorithm, finally use SIFT achieve the face detection function.

A Realization of Face Detection System Based on ARM Linux

In order to adapt to the requirements of intelligent video monitoring system, this paper presents an ARM-Linux based video monitoring system for face detection. In this system, an ARM processor with a Linux operating system was used, and the USB camera was used to capture data, and then the face detection was conducted in the ARM device. The OpenCV library was transplanted to Linux embedded system. The algorithm of face detection was realized by calling the OpenCV library. Specially, adaboost algorithm was chose as the face detection algorithm. Experimental results show that the face detection effect of the system is satisfactory and can meet the real time requirement of video surveillance.

Implementation and optimization of face recognition algorithm based on DSP

In order to realize the real-time face recognition in video by embedded system,the design scheme of fast face recognition system based on TI TMS320DM642 was presented,and optimization policy was proposed in terms of both hardware and software.Firstly,effective features were selected,and the algorithm of face detection and recognition was briefly introduced,then according to the algorithm,the design scheme and function units of hardware system were described.Finally,the algorithm was transplanted onto the hardware system,then the optimization policy was applied,and fast embedded face recognition system was implemented.The experimental results demonstrate the system works reliably,the running speed of algorithm was improved markedly,and real-time face recognition in video was realized.