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Low cost and processor efficient facial recognition system

机译:低成本和处理器高效的面部识别系统

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The objective of this research project is to develop a system with a webcam and efficiently detect faces of persons preciously loaded in the database. This project aims towards the use of facial recognition using mundane processors and hence the system is optimized and reviews the grand challenges that are faced for developing such a system and a literary survey that has provided a crucial insight in the developing of the system. Viola Jones Algorithm has been utilized to detect a face within a picture and ECOC for training to fit multi class models into categories or code-words. With the algorithm and the code as suggested in this paper, results are projected towards various lighting conditions of front profile of faces. Under normal lighting conditions a very high detection rate of has been obtained. Under partial exposure a lower detection rate has been obtained and at overexposed conditions detection rate similar to normal lighting conditions has been obtained. The rejection rate is however, cent percent in all three conditions mentioned. There is ample scope for implementing recognition techniques.
机译:该研究项目的目的是开发一个具有网络摄像头的系统,并有效地检测数据库中宝贵的人员的面部。该项目旨在使用采用普通处理器的面部识别技术,因此该系统得到了优化,并回顾了开发这种系统和文学调查所面临的巨大挑战,这为系统的开发提供了至关重要的见识。 Viola Jones算法已被用于检测图片和ECOC中的面部,以进行训练以使多类模型适合类别或代码字。利用本文建议的算法和代码,将结果投影到人脸正面轮廓的各种照明条件下。在正常照明条件下,已经获得了很高的检测率。在部分曝光下,可获得较低的检测率,而在曝光过度的条件下,可获得与正常照明条件相似的检测率。但是,在上述所有三种情况下,废品率均为百分之一。有足够的空间来实施识别技术。

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