The Research of Smart Surveillance System Using Hadoop Based On Craniofacial Identification

Systems operating in a distributed environment need to maintain high standards regarding availability and performance. A decretive concern in distributed computing systems is to efficiently schedule the tasks among all processors so that the overall processing time of the submitted tasks is at a minimum. The increasing need for intelligent visual surveillance in commercial, law enforcement and military applications makes automated visual surveillance systems one of the main current application domains in computer vision. Parallel Hadoop implementation is better suited for large data sizes than for when a computationally intensive application is required. In this paper, we propose a probabilistic approach for face recognition suitable for a multi-camera video surveillance network using Hadoop platform. This proposed design of a hybrid intelligent surveillance system which the face detection and tracking is required for Video Surveillance to capture people. The surveillance deals with the extraction of face datasets from a video and processing of images using a Hadoop image processing interface and craniofacial identification based facial feature extraction.