澳洲酒店管理论文代写-人脸识别结构

本文主要讲的是人脸识别结构,人脸识别是一项非常具有挑战性的技术,在计算机科学、视觉和模式识别技术等领域有着非常重要的研究课题。这是因为面部识别会受到姿势、光照和面部表情的影响。从执法到商业,从娱乐到社交媒体,有许多新兴的应用和需求。人脸识别是行业最重要的需求(Wang et al., 2014)。自动高效的人脸识别是当今世界的主要需求。本篇澳洲酒店管理论文代写文章由澳洲论文通AssignmentPass辅导网整理,供大家参考阅读。

Face recognition is a very challenging technology that has very significant topic of research in the area of computer science, vision and pattern recognition techniques. This is because face recognition can be affected by the pose, illumination and facial expression. There are many emerging applications and requirements from law enforcement to commercial requirement and from entertainment to social media. Face recognition is the most important demand of the industry (Wang et al., 2014). The automated and efficient face recognition is the major demand in the contemporary world.
There has been significant research done on the face recognition. Several researchers have worked to solve the problems, yet there are many challenges in the face recognition technology that are required to be resolved. Some of the significant issues that are aced during face recognition are change of the pose, expressions of face, illumination of the scene and orientation (Wang et al., 2014). It has been noticed that when size of the face database increases, the face recognition time becomes a big problem.
Face recognition or the face representation is significantly used in various circumstances as the non contact biometrics. The conventional method of face recognition could not justify the current demands of the market (Kasar et al., 2016). This is because the conventional method produced very low accuracy and it was even restricted at various occasions. The unrestricted face recognition requires significant efforts and techniques. However, the current technology in face recognition is successful in producing high accuracy and low intrusiveness. Face recognition has produced the accuracy of the “physiological approach without being intrusive” (Kasar et al, 2016, p. 83). This has been the reason that face recognition has drawn the attention of the researchers from the field of psychology, security, criminal studies, image processing and computer vision. Face recognition is produced in various algorithms and has proved to be very important in the multimedia image processing.
The technique of face recognition analyses various characteristics of the image of different faces. These images are produced through the input of the idea cameras and through online image capturing. However, the state of the art technology of the face recognition is done and it has advanced by the development of the deep learning (Sun et al., 2015). Face recognition technology has also been introduced for the verification of the actual identity of the person. This technology is specifically based on the field of Biometrics. According to Kasar et al. (2016), “Biometrics is a technique for identifying people by using a unique physiological characteristic, such as a fingerprint, eye, face, etc. or behavioural characteristics, e.g., voice and signature etc” (p. 82). In simple words, it can be said that Biometrics is the use of computer for face recognition. There are four main elements of the biometric system that includes Face Detection, Pre-processing, Feature Extraction and Face Recognition.

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