US 7,050,607 B2Granted

System and method for multi-view face detection

AssigneeMicrosoft Corporation

InventorsZiQing Li, HongJiang Zhang, ZhenQiu Zhang

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Abstract

A system and method for real-time multi-view (i.e. not just frontal view) face detection. The system and method uses a sequence of detectors of increasing complexity and face/non-face discriminating thresholds to quickly discard non-faces at the earliest stage possible, thus saving much computation compared to prior art systems. The detector-pyramid architecture for multi-view face detection uses a coarse-to-fine and simple-to-complex scheme. This architecture solves the problem of lengthy processing that precludes real-time face detection effectively and efficiently by discarding most of non-face sub-windows using the simplest possible features at the earliest possible stage. This leads to the first real-time multi-view face detection system which has the accuracy almost as good as the state-of-the-art system yet 270 times faster, allowing real-time performance.

Claims13

Dependent claims

A computer-implemented face detection process for detecting a person's face in an input image and identifying a face pose range into which the face pose exhibited by the detected face falls, comprising using a computer to perform the following process actions:

creating a database comprising a plurality of training feature characterizations, each of which characterizes the face of a person at a known face pose or a non-face;
training a plurality of detectors arranged in a pyramidal architecture comprising three detector layers and wherein said first detector layer comprises a single full-view detector responsible for the full range of −90 to 90 degrees of face pose, with 0 degrees being frontal view;
said second detector layer comprises a first, second and third detector, said first detector being capable of detecting face pose ranges of −90 to 40 degrees, said second detector being capable of detecting face pose ranges of −30 to 30 degrees, and said third detector being capable of detecting face pose range of 40 to 90 degrees;
said third detector layer comprising nine detectors, capable of detecting face pose ranges of −90 to −80 degrees, −70 to −60 degrees, −50 to −40 degrees, −30 to −20 degrees, −10 to 10 degrees, 20 to 30 degrees, 40 to 50 degrees, 60 to 70 degrees, and 80 to 90 degrees, respectively, to determine whether a portion of an input image depicts a person's face having a face pose falling within a face pose range associated with one of the detectors using the training feature characterizations;
and wherein
said detectors using a greater number of feature characterizations are arranged at the bottom of the pyramid, and wherein
said detectors arranged to detect finer ranges of face pose are arranged at the bottom of the pyramid;
inputting a portion of an input image into the plurality of detectors arranged in a pyramid architecture;
and
interpreting the output of the plurality of detectors to determine whether the portion of the input image contains a face and if so to identify the pose associated with each detected face.

7 more elements

creating a database comprising a plurality of training feature characterizations, each of which characterizes the face of a person at a known face pose or a non-face;
training a plurality of detectors arranged in a pyramidal architecture to determine whether a portion of an input image depicts a person's face having a face pose falling within a face pose range associated with one of the detectors using the training feature characterizations;
and wherein
said detectors using a greater number of feature characterizations are arranged at the bottom of the pyramid, and wherein
said detectors arranged to detect finer ranges of face pose are arranged at the bottom of the pyramid;
inputting a portion of an input image into the plurality of detectors arranged in a pyramid architecture, wherein inputting a portion of an input image into the plurality of detectors arranged in a pyramid architecture further comprises arbitrating between two or more detectors that detect a face in the same detector layer to determine if the detections represent two different faces or two detections of one face, wherein arbitrating between two or more detectors further comprises
determining if the detections by each of the two or more detectors overlap;
specifying that if the detections by each of the two or more detectors do not overlap then arbitration is not necessary and each face detection is determined to be a separate face;
combining the output of some of the detector view ranges into one class by creating new classes of view ranges from the various pose range detectors at the detector pyramid's outputs;
arbitrating between the new classes of view ranges to categorize each overlapping detection into one of the new classes of view ranges;
and
interpreting the output of the plurality of detectors to determine whether the portion of the input image contains a face and if so to identify the pose associated with each detected face.

9 more elements

Dependencies are inferred from the claim text.

Facts

Application: 10/091,100Filed 4 Mar 2002 · us provisional application
Priority: 8 Dec 2001
Published: US 2003/0108244 A112 Jun 2003
Granted: 23 May 2006
Term ends: Not estimatedThe source records don’t support an estimate.

Classification6 codes

G06V 40/161
Human faces, e.g. facial parts, sketches or expressions: detection; Localisation; Normalisation
G06F 18/214
Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation: generating training…
G06F 18/24765
Classification techniques: rule-based classification
G06V 10/446
By matching or filtering: using Haar-like filters, e.g. using integral image techniques