Child Missing with Surveillance Analysis with Multi Phase Extraction Face Monitoring

Abstract

Abstract: Visual Surveillance has been placed in everywhere for any incidents identification. With the wide developments missing child identification with the computer vision system is the main focus. The implementation carried out with face based detection with rapid advance digital connectivity. Face recognition plays as a major developmental process where the concern person can be identified with face based identification system. Machine learning with artificial intelligence plays a vital role in facial detection and recognition. The paper proposes Haar Cascade on feature extraction from facial points and Hybrid Recurrent Neural System(HRNN) with Long Short Term Memory(LSTM) algorithm, on multi face recognition over public crowded area. Missing child images will be pre- trained in a database where the face matching templates will be provided. On matching the database labeled points with the feature point an E-mail or SMS based alert system can be generated on notification to the authority with cam points. Thus the development carried will give best accuracy solution on finding out from multiple face regions. Mainly identification of the missing child over the road side areas will be done with computer vision frame targeting system.