IMAGE RECOGNITION APPARATUS FOR IDENTIFYING FACIAL EXPRESSION OR INDIVIDUAL, AND METHOD FOR THE SAME

• US 20100296706A1
• Filed: 05/17/2010
• Published: 11/25/2010
• Est. Priority Date: 05/20/2009
• Status: Abandoned Application

• Current Assignee: Canon Kabushiki Kaisha (Canon Inc.)
• Original Assignee: Canon Kabushiki Kaisha (Canon Inc.)
• Inventors: Matsugu, Masakazu, Kaneda, Yuji, Mori, Katsuhiko
• Application Number:
  US12/781,728
• Publication Number:
  US 20100296706A1
• Time in Patent Office: Days
• US Class Current: 382/118
• CPC Class Codes: G06V 10/46 Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]; Salient regional features colour feature extraction G06V10/56
• CPC Class Codes: G06V 10/50 by performing operations within image blocks; by using histograms, e.g. histogram of oriented gradients [HoG]; by summing image-intensity values; Projection analysis
• CPC Class Codes: G06V 40/171 Local features and components; Facial parts eye characteristics G06V40/18; Occluding parts, e.g. glasses; Geometrical relationships
• CPC Class Codes: G06V 40/176 Dynamic expression

Abstract

A face detecting unit detects a person'"'"'s face from input image data, and a parameter setting unit sets parameters for generating a gradient histogram indicating the gradient direction and gradient magnitude of a pixel value based on the detected face. Further, a generating unit sets a region (a cell) from which to generate a gradient histogram in the region of the detected face, and generates a gradient histogram for each such region to generate feature vectors. An expression identifying unit identifies an expression exhibited by the detected face based on the feature vectors. Thereby, the facial expression of a person included in an image is identified with high precision.

Claims

1. An image recognition apparatus comprising:

a detecting unit constructed to detect a person'"'"'s face from input image data;

a parameter setting unit constructed to set parameters for generating a gradient histogram indicating gradient direction and gradient magnitude of a pixel value based on the face detected by the detecting unit;

a region setting unit constructed to set, in the region of the detected face, at least one region from which the gradient histogram is to be generated, based on the parameters set by the parameter setting unit;

a generating unit constructed to generate the gradient histogram for each of the regions set by the region setting unit, based on the parameters set by the parameter setting unit; and

an identifying unit constructed to identify the detected face using the gradient histogram generated by the generating unit.

2. The image recognition apparatus according to claim 1, further comprising a calculating unit constructed to calculate the gradient direction and gradient magnitude for the region of the detected face based on the parameters set by the parameter setting unit,

wherein the generating unit generates the gradient histogram using the calculated gradient direction and gradient magnitude.

3. The image recognition apparatus according to claim 1, further comprising a first normalizing unit constructed to normalize the region of the detected face so that the detected face has a predetermined size and a predetermined orientation,

wherein the region setting unit sets, in the normalized region of the face, at least one region from which the gradient histogram is to be generated.

4. The image recognition apparatus according to claim 1, further comprising a second normalizing unit constructed to normalize the gradient histogram generated by the generating unit for each of the regions set by the region setting unit,

wherein the identifying unit identifies the detected face using the normalized gradient histogram.

5. The image recognition apparatus according to claim 1, further comprising:

an extracting unit constructed to extract a plurality of regions from the region of the detected face; and

a weighting unit constructed to weight the gradient histogram for each of the regions extracted by the extracting unit.

6. The image recognition apparatus according to claim 1, further comprising an image generating unit constructed to generate images of different resolutions from the region of the detected face,

wherein the identifying unit identifies the detected face using gradient histograms generated from the generated images of different resolutions.

7. The image recognition apparatus according to claim 1, wherein the parameters set by the parameter setting unit are an area for calculating the gradient direction and the gradient magnitude, a size of a region to be set by the region setting unit, a width of bins in the gradient histogram, and a number of gradient histograms to be generated by the generating unit.

8. The image recognition apparatus according to claim 2, wherein the calculating unit calculates the gradient direction and the gradient magnitude by making reference to values of top, bottom, left, and right pixels positioned at a predetermined distance from a predetermined pixel.

9. The image recognition apparatus according to claim 1, wherein the gradient histogram is a histogram whose horizontal axis represents the gradient direction and vertical axis represents the gradient magnitude.

10. The image recognition apparatus according to claim 1, wherein the identifying unit identifies a person'"'"'s facial expression or an individual.

11. An imaging apparatus comprising:

an imaging unit constructed to capture an image of a subject and generate image data;

a detecting unit constructed to detect a person'"'"'s face from the image data generated by the imaging unit;

a parameter setting unit constructed to set parameters for generating a gradient histogram indicating gradient direction and gradient magnitude of a pixel value based on the face detected by the detecting unit;

a region setting unit constructed to set, in the region of the detected face, at least one region from which the gradient histogram is to be generated, based on the parameters set by the parameter setting unit;

a generating unit constructed to generate the gradient histogram for each of the regions set by the region setting unit, based on the parameters set by the parameter setting unit;

an identifying unit constructed to identify the detected face using the gradient histogram generated by the generating unit; and

an image recording unit constructed to record the image data if the identification made by the identifying unit shows a predetermined result.

12. An image recognition method comprising:

detecting a person'"'"'s face from input image data;

setting parameters for generating a gradient histogram indicating gradient direction and gradient magnitude of a pixel value, based on the detected face;

setting, in the region of the detected face, at least one region from which the gradient histogram is to be generated, based on the set parameters;

generating the gradient histogram for each of the set regions, based on the set parameters; and

identifying the detected face using the generated gradient histogram.

14. A computer-readable storage medium that stores a computer program for causing a computer to execute the method according to claim 12.

13. An imaging method comprising:

capturing an image of a subject to generate image data;

detecting a person'"'"'s face from the generated image data;

setting parameters for generating a gradient histogram indicating gradient direction and gradient magnitude of a pixel value, based on the detected face;

setting, in the region of the detected face, at least one region from which the gradient histogram is to be generated, based on the set parameters;

generating the gradient histogram for each of the set regions, based on the set parameters;

identifying the detected face using the generated gradient histogram; and

recording the image data if the identification shows a predetermined result.

15. A computer-readable storage medium that stores a computer program for causing a computer to execute the method according to claim 13.