Affiliation:
1. Sam Houston State University, USA
Abstract
Computer vision is a research field in computer science that provides the computer the ability of human perceptions. The goal of computer vision is to understand the image and its contents. Computer vision has evolved from simple pattern recognition to solving various complex real-world problems. Nowadays, computer vision has its application to the various domains of scientific areas not limited to Computer Science. It is widely used for medical science, biology, physics, and chemistry as well. The recent boost in computer vision is the due influence of machine learning (ML). ML is a subfield of artificial intelligence. Machine learning is a method that makes a computer learn from the provided data and improve its performance with time. Computer vision problems are complex, and they require a correct choice of algorithms. In this chapter, some machine learning algorithms that are widely used in computer vision will be discussed. The theoretical concepts are related to real-world computer vision problems such as human skin detection.
Reference35 articles.
1. Organization of the ABCR gene: Analysis of promoter and splice junction sequences.;R.Allikmets;Gene,1998
2. k-means++: The advantages of careful seeding.;D.Arthur;Proceedings of the eighteenth annual acm-siam symposium on discrete algorithms,2007
3. BerryM. J.LinoffG. S. (2004). Data mining techniques: for marketing, sales, and customer relationship management. John Wiley & Sons.
4. Do mixture models in chromaticity space improve skin detection?
5. Chai, D., Phung, S. L., & Bouzerdoum, A. (2001). Skin color detection for face localization in human-machine communications. In Proceedings of the sixth international symposium on signal processing and its applications (cat. no. 01ex467) (Vol. 1, pp.343–346). Academic Press.
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