REAL TIME OBJECT DETECTION WITH DEEP LEARNING









Abstract

Real time object detection is a vast, vibrant and sophisticated area of computer vision aimed towards object identification and recognition. Object detection detects the semantic objects of a class objects using OpenCV (Open source Computer Vision), which is a library of programming functions mainly trained towards real time computer vision in digital images and videos. Visually challenged people cannot distinguish the objects around them. The main aim behind this real time object detection is to help the blind to overcome their difficulty. Real time object detection finds its uses in the areas like tracking objects, video surveillance, pedestrian detection, people counting, self-driving cars, face detection, ball tracking in sports and many more. This is achieved using Convolution Neural Networks, which is a representative tool of Deep learning. This project acts as an aiding tool for visually challenged people.


Modules


Algorithms


Software And Hardware