document: This paper suggests a design of high quality real-time rotation face detection architecture for gesture recognition of smart TV. For high performance rotated face detection, the multiple-MCT(Modified Census Transform) architecture, which is robust against lighting change, was used. The Adaboost learning algorithm was used for creating optimized learning data. The proposed hardware structure was composed of Color Space Converter, Image Resizer, Noise Filter, Memory Controller Interface, Image Rotator, Image Scaler, MCT Generator, Candidate Detector, Confidence Switch, Confidence Mapper, Position Resizer, Data Grouper, Overlay Processor and Color Overlay Processer. As a result, suggested face detection device can conduct real-time processing at speed of at least 30 frames per second.
extractive_keyphrases: adaboost learning algorithm color overlay processer color space converter confidence switch creating optimized learning data data grouper face detection gesture recognition hardware structure image rotator image scaler mct memory controller interface noise filter overlay processor
abstractive_keyphrases: candidate detector, confidence mappe design of high quality real-time rotation face detection architecture for gesture recognition of smart tv image resizer, mct generator modified census transform position resizer, real-time processing rotation face detection architecture