Image recognition apparatus, image recognition method, and program
In the present disclosure, an image parameter of an input image is changed, features is extracted from each of a plurality of generated images, a category of each region is determined based on the features in each image, and the results are integrated.
1. An image recognition apparatus comprising:
one or more processors; and
a memory coupled to the one or more processors, the memory having stored thereon instructions which, when executed by the one or more processors, cause the apparatus to:
acquire an image;
generate a plurality of variation images by changing a parameter of the acquired image into each of different parameters;
extract features from each of the plurality of variation images;
perform regcognition on each of the plurality of variation images based on the extracted features; and
integrate recognition results of the plurality of variation images into an integrated recognition result,
wherein the recognition results of the plurality of variation images are integrated by using a classifier that has been trained to decrease a difference between an output of the classifier and a supervisory value of learning data.
2. The image recognition apparatus according to claim 1 , wherein the recognition is performed to discriminate categories of regions included in the image.
3. The image recognition apparatus according to claim 1 , wherein the recognition is performed to discriminate types of scenes of the image.
4. The image recognition apparatus according to claim 1 , wherein the recognition is performed to detect a specific object included in the image.
5. The image recognition apparatus according to claim 1 , wherein the recognition is performed to detect a main object included in the image.
6. The image recognition apparatus according to claim 1 , wherein the classifier has learned in advance to further use any of the parameter about an image, camera information during image capturing, or a recognition result of an image as input and a supervisory value as a target value, and to output the integrated recognition result.
7. The image recognition apparatus according to claim 1 , wherein recognition results of the plurality of images are integrated stepwise.
8. The image recognition apparatus according to claim 1 , wherein the change of parameter includes at least one of a change of an exposure value of the image, a change of a brightness value of the image, transformation of the image, clipping of the image, addition of noise to the image, addition of blur to the image, and a change of a focal position of the image.
9. The image recognition apparatus according to claim 1 , wherein the memory further stores instructions which, when executed by the one or more processors, cause the apparatus to acquire a plurality of images by changing the parameters of the images during image capturing.
10. The image recognition apparatus according to claim 1 , wherein the memory further stores instructions which, when executed by the one or more processors, cause the apparatus to acquire a plurality of images by changing the parameters of the images after image capturing.
11. An image recognition method, comprising:
acquiring an image;
generating a plurality of variation images by changing a parameter of the acquired image into each of different parameters;
extracting features from each of the plurality of variation images;
performing recognition on each of the plurality of variation images based on the extracted features; and
integrating recognition results of the plurality of variation images into an integrated recognition result, wherein the recognition results of the plurality of variation images are integrated by using a classifier that has been trained to decrease a difference between an output of the classifier and a supervisory value of learning data.
12. A computer readable storage medium storing a program which causes a computer to execute a method of image recognition, the method comprising;
acquiring an image;
generating a plurality of variation images by changing a parameter of the acquired image into each of different parameters;
extracting features from each of the plurality of variation images;
performing recognition on each of the plurality of variation images based on the extracted features; and
integrating recognition results of the plurality of variation images into an integrated recognition result, wherein the recognition results of the plurality of variation images are integrated by using a classifier that has been trained to decrease a difference between an output of the classifier and a supervisory value of learning data.