Theft Detection System using Convolutional Neural Network and Object Tracking

Computer Engineering

Todaymodernworldishighlydigitalandhighly connected generating enormous data over the internet with high speed. Such data has led many researchers, scientific professionals to explore this data to enable computing machines to understand the real world as a real human being does. Image processing has been explored as the field to provide machines with a vision of their own of which object detection and its tracing throughout the frame has emerged as the most important and vastly explored topic. In recent years due to the great ability and power with feature learning of the Convolutional Neural network (CNN) it has received an overwhelming interest from the computer vision community, leading through many significant breakthroughs. Firstly the paper will introduce the basic building blocks of CNN. Secondly this paper will dive into the object detection practices which then will lead us to object tracking. Finally the paper will be explain how a theft can be detected by combining object detection and object tracking methodologies.

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