Detecting faces in images: A survey

Detecting faces in images: A survey (2002)

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by Ming-hsuan Yang , David J. Kriegman , Narendra Ahuja

Venue:	IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
Citations:	437 - 4 self

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Datum	Value	Source
TITLE	Detecting faces in images: A survey	INFERENCE
AUTHOR NAME	Ming-hsuan Yang	user correction
AUTHOR NAME	David J. Kriegman	user correction
AUTHOR NAME	Narendra Ahuja	user correction
ABSTRACT	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 three-dimensional position, orientation, and the lighting conditions. Such a problem is challenging because faces are nonrigid 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.	user correction
YEAR	2002	INFERENCE
VENUE	IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE	user correction
VENUE TYPE	JOURNAL	INFERENCE
VOLUME	24	user correction
NUMBER	1	user correction
CITATIONS	181 found	ParsCit 1.0