Detecting faces in images: a survey
Ming-Hsuan Yang; Kriegman, D.J.; Ahuja, N.
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Volume 24, Issue 1, Jan 2002 Page(s):34 - 58
Digital Object Identifier 10.1109/34.982883
Summary:Images containing faces are essential to intelligent vision-based
human-computer interaction, and research efforts in face processing
include face recognition, face tracking, pose estimation and expression
recognition. However, many reported methods assume that the faces in an
image or an image sequence have been identified and localized. To build
fully automated systems that analyze the information contained in face
images, robust and efficient face detection algorithms are required.
Given a single image, the goal of face detection is to identify all
image regions which contain a face, regardless of its 3D position,
orientation and lighting conditions. Such a problem is challenging
because faces are non-rigid and have a high degree of variability in
size, shape, color and texture. Numerous techniques have been developed
to detect faces in a single image, and the purpose of this paper is to
categorize and evaluate these algorithms. We also discuss relevant
issues such as data collection, evaluation metrics and benchmarking.
After analyzing these algorithms and identifying their limitations, we
conclude with several promising directions for future research
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