Object Detection in a Video

Object Detection and classification are the successful applications of image analysis and algorithm-based understanding that can be applied to an image or on a video related to computer vision in biometric research. It has enormous application value and market potential which involves deep learning and OpenCV techniques. OpenCV and python programming development is used for designing real face recognition systems. It provides access to machine-based in-depth analysis of a person's facial features. The main algorithm used for detecting the identity is the SSD algorithm. All in all, the machine successfully identifies any entity by using the combination of SSD and MobileNets. The detection module, training module and recognition module are the three major modules that are involved in the facial recognition and detection process. The main concept of our project is to train the model with some datasets with various identities and then test the model. The model will detect and recognize the identities of faces which are previously trained. This will result in image classification along with the localization. It will help to detect whether the person or the object which we a researching for, is present or not in that image or a video.