Face detection in resource constrained wireless systems

Abstract

Face detection is one of the most popular areas of computer vision partly due to its many applications such as surveillance, human-computer interaction and biometrics. Recent developments in distributed wireless systems offer new embedded platforms for vision that are characterized by limitations in processing power, memory, bandwidth and available power. Migrating traditional face detection algorithms to this new environment requires taking into consideration these additional constraints. In this chapter, we investigate how image compression, a key processing step in many resource-constrained environments, affects the classification performance of face detection systems. Towards that end, we explore the effects of three well known image compression techniques, namely JPEG, JPEG2000 and SPIHT on face detection based on support vector machines and Adaboost cascade classifiers (Viola-Jones). We also examine the effects of H.264/MPEG-4 AVC video compression on Viola-Jones face detection. © 2010 Springer-Verlag.