Many current human face detection algorithmsmake implicit assumptions about the scale, orientation or viewpoint of faces in an image and exploit these constraints to detect and lo...
Although many face detection algorithms have been introduced in the literature, only a handful of them can meet the real-time constraints of mobile devices. This paper presents th...
Mohammad Rahman, Jianfeng Ren, Nasser D. Kehtarnav...
Markov Random Fields (MRFs) are proposed as viable stochastic models for the spatial distribution of gray level intensities for images of human faces. These models are trained usi...
Face detection is important in many algorithms in the areas of machine object recognition and pattern recognition. The kaleidoscope of applications for face detection extends acro...
A novel algorithm, termed a Boosted Adaptive Particle Filter (BAPF), for integrated face detection and face tracking is proposed. The proposed algorithm is based on the synthesis ...
The spatial distribution of gray level intensities in an image can be naturally modeled using Markov Random Field (MRF) models. We develop and investigate the performance of face ...
Face detection has advanced dramatically over the past three decades. Algorithms can now quite reliably detect faces in clutter in or near real time. However, much still needs to ...