Transcription of CNNs for Face Detection and Recognition
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CNNs for Face Detection and Recognition
CNNs for Face Detection and RecognitionYicheng AnDepartment of Electrical EngineeringStanford WuDepartment of Electrical EngineeringStanford YueDepartment of Electrical EngineeringStanford face Detection method is becoming a more andmore important technique in our social lives. From face de-tection technology implemented in our cheap cameras to in-telligent agencies sophisticated global skynet surveillancesystem, such techniques have been widely used in a largenumber of areas and the market is still growing with a highspeed. Face Detection has been an active research area withmany successful traditional and deep learning methods. Inour project we are introducing new convolutional neuralnetwork method to tackle the face Detection to maintain ahigh accuracy while running in real Problem StatementIn our imaginary scenario, our technique could be usedby companies and facilities with security levels: customerscould put all personnel s info into the dataset, and then putthe camera at the desired position like the office front people coming in are not in the dataset, there would be analarm; otherwise, everything should be , our method has mainly 2 steps and 1 require-ment, the first step should be localization, which means thesystem could localize faces and then circle them out
runtime is still dominated by region proposals method. 2.3. Detection without Proposals Some detection methods were introduced without the Region Proposal method in order to achieve smaller training and testing time. YOLO [1] and SSD [5] are two detection methods without Region Proposals. The input image goes
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