Pattern Recognition Camera Using Deep Learning Project
Abstract
Efficient and accurate object detection has been an important topic in the advancement of computer vision systems. With the advent of deep learning techniques, the accuracy for object detection has increased drastically.
The project aims to incorporate state-of-the-art technique for object detection. with the goal of achieving high accuracy with a real-time performance.A major challenge in many of the object detection systems is the dependency on other computer vision techniques for helping the deep learning based approach, which leads to slow and non-optimal performance.
In this project, we use a completely deep learning based approach to solve the problem of object detection in an end-to-end fashion.The resulting system is fast and accurate, thus aiding those applications which require object detection.
An accurate and efficient object detection system has been developed which achieves comparable metrics with the existing state-of-the-art system. This project uses recent techniques in the field of computer vision and deep learning.
An important scope would be to train the system on a video sequence for usage in tracking applications. Addition of a temporally consistent network would enable smooth detection and more optimal than per-frame detection.
Detecting objects and tracking while it is in motion is very helpful for both military and commercial applications. The main purpose of this project is to make object detection and tracking based surveillance systems accessible for everyone.
The main objective in this paper is to increasing the number of surveillance systems. which uses real time object detection and tracking on field applications. Real time object detection and tracking on video stream is a very crucial topic of surveillance systems in field applications. To easily accessible product, the project constructed as low cost project. In this project, several methods are presented. We implemented different detecting and tracking methods.
