A Unified Streaming Architecture for Real Time Face Detection and Gender Classification
Kevin M. Irick, Michael DeBole, Vijaykrishnan Narayanan, Rajeev Sharma, Hankyu Moon, Satish Mummareddy · 2007
An integral part of interactive computing environments are systems that have the ability to process information about their users in real-time. In many cases it is desirable to not only recognize a human user but also to extract as much information about the user as possible, such as gender, ethnicity, age, etc. In this paper we present an FPGA implementation of a neural network configured specifically for performing face detection and gender classification in real-time video streams. Our streaming architecture performs the face and gender classification tasks at 30 frames per second on a small sized Virtex-4 FPGA, at accuracy comparable to that of a leading commercial software implementation.