Abstract
Object detection is an active area of research with rapid growth in the number of new publications. It is a computer vision technique widely used in various domains and it forms a foundation for a variety of applications, such as face detection and autonomous driving. The precondition for successful object detection are efficient algorithms that are able to detect features related to a certain object in static or moving images and the processing power which ensures a fast execution. This paper provides an overview of the current most significant visual object detection algorithms, their essential features, their advantages, limitations, as well as datasets used for their training and evaluation. Based on the provided overview, this paper attempts to also recognize directions for further development and contribution to the area.
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