Theft Detection Using Artificial Intelligence Video Retrieval Technique

Abstract: Video-based facial recognition has gotten a lot of interest in recent years due to its wide range of applications. Face identification is complicated by the significant diversity of pictures caused by position changes, lighting conditions, facial emotions, and image occlusion. Surveillance and mobile cameras, on the other hand, are low-cost equipment that cause significant motion blur, out-of-focus blur, and a broad range of posture variation, lowering video frame quality. Face recognition from video image processing is achieved using machine learning techniques. Image capture, segmentation, feature extraction, classification, and face detection are all processes in the process. The retrieved characteristics are used to train classifiers for pictures that have been processed. As a result, the most current algorithms produced provide an overview of the state of the art in video facial recognition technology.

Keywords: Face detection, security monitoring, video retrieval, face recognition.