Face detection

Fig. 7.3 Experimental setup for the nanosecond laser Flash Photolysis with a white light continuum. A Brilland-Quantel Nd YAG laser delivers the fundamental pulses (355 and 532 nm). A pulsed XBO lamp is used as white light source. The laser signal is split in order to trigger the digital storage oscilloscope (DSO) utilizing a second photodiode (PD). Two separate detection units in different geometries—photomultiplier (PMT) in front face and a PD in side face—detect the signal in the UV/vis and NIR region, respectively. The monochromator is operated by a standard PC...

Figure 150 Different radiative modes in organic LEDs. External modes available for the face detection ] constitutes only a fraction of light generated in the EML, the remainder being lost due to various wave guide modes indicated in the figure.

Furthermore, for the face detected emission (as usually is the case), the light output coupling factor (287) reduces the measured Oel to OgE, so that we deal with the external quantum EL efficiency... 

Koha, L.H., Ranganath, S. and Venkatesh, Y.V. (2002) An integrated automatic face detection and recognition system. Pattern Recognition, 35 1259-1273. 

Bazanov, P.V., Buryak, D.Y., Mun, W.J., Murynin, A.B. and Yang, H.K. (2005) Comparison of Gabor wavelet and neural network-based face detection algorithms. In Signal and Image Processing (ed M.W. Marcellin), ACTA Press, Honolulu, Hawaii, pp. 200-208. 

Face Detection for Drivers Drowsiness Using Computer Vision... 

This paper proposes a computer vision based driver drowsiness system, use of OpenCV in image processing, interfacing of web camera to OpenCV, Haar classifiers like feature based face detection methods, eyelid identification, and developing alertness system using eyelid status to warn the driver accordingly by providing an alarm. 

The remainder of this paper is organized as follows. Section II describes the different techniques for detecting drowsy driver and significance of the problem. In Section III describes proposed system structure, system flowchart and introduction to OpenCV. In Section IV describes the interfacing of web camera to OpenCV. Section V Haar classifiers like feature based face detection techniques. In Section VI describes the results and finally we make conclusion in Section VII. 

Face detection is the process of detecting faces in images or videos. Face detection in this project is carried out using the OpenCV library [14]. 

This section describes the result of interfacing of Web Cam to OpenCV shown in figure 4 and face detection algorithm using haar-like classifiers features shown in figure 5 ... 

Fig. 5 Face detection using Haar-like features...

Hyun Hoi James Kim, Survey paper Face Detection and Face Recognition , In Pixx eedings, Intmiational Conference on Computing and Video Prox essing, pp 2245-2252. 

Nusirwan Anwar bin Abdul Rahman, Kit Chong Wei and John See, RGB-H-CbCr Skin Color Moxlel for Human Face Detection , Faculty of hrfoxmation Technology, Multimedia University. 

Paul Viola and Michael J. Jones, Robust Real-Time Face Detection , International Journal of Computer Vision 57(2), 2004, pp 137-154. 

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