Over recent years automated face detection and recognition (FDR) have gained significant attention from the commercial and research sectors. This paper presents an embedded face de...
Abbas Bigdeli, Colin Sim, Morteza Biglari-Abhari, ...
Effective and real-time face detection has been made possible by using the method of rectangle Haar-like features with AdaBoost learning since Viola and Jones’ work [12]. In this...
Abstract. This paper describes Pittsburgh Pattern Recognition’s participation in the face detection and tracking tasks for the CLEAR 2007 evaluation. Since CLEAR 2006, we have ma...
Michael C. Nechyba, Louis Brandy, Henry Schneiderm...
This paper presents the algorithm and evaluation results of a face detection and tracking system. A tree-structured multi-view face detector trained by Vector Boosting is used as t...
Face detection and tracking, through image sequences, are primary steps in many applications such as video surveillance, human computer interface, and expression analysis. Many cu...
Human detection under occlusion is a challenging problem in computer vision. We address this problem through a framework which integrates face detection and person detection. We ï¬...
William Robson Schwartz, Raghuraman Gopalan, Rama ...
This paper presents a hardware architecture for face detection based system on AdaBoost algorithm using Haar features. We describe the hardware design techniques including image s...
Junguk Cho, Shahnam Mirzaei, Jason Oberg, Ryan Kas...
We present an algorithm to estimate the 3D pose (location
and orientation) of a previously unseen face from low-quality range images. The algorithm generates many pose candidates ...
We present a real-time algorithm to estimate the 3D
pose of a previously unseen face from a single range im-
age. Based on a novel shape signature to identify noses in
range ima...
We describe an automatic method for beautifying digital portraits by smoothing the skin of the face. The method builds on existing face detection and face feature alignment techno...