CROSS REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of Chinese patent application no. 201710914591.7, filed Sep. 30, 2017, which is hereby incorporated by reference herein in its entirety.

BACKGROUND OF THE INVENTION

Field of the Invention

The present invention relates to image processing, especially relates to a recognition apparatus and a recognition method.

Description of the Related Art

Since human attributes commonly refer to facial appearances and/or body appearances that could depict a person, human attribute recognition is generally used for human behaviour analysis (e.g. people attribute counting, people tracking, crowd analysis). Wherein, the facial appearances comprise the person's age, the person's gender, and the person's race for example. The body appearances comprise body height of the person and body weight of the person for example.

One exemplary human attribute recognition technique is disclosed in U.S. Pat. No. 9,002,116B2 which mainly comprises: firstly finding similar images (e.g. the ranked top N images) which have similar facial appearances to a person in an inputted image from a storage device according to feature matching, and then estimating the facial attribute (e.g. the age) of the person in the inputted image based on the facial attributes (e.g. the ages) of the persons in the similar images.

That is to say, the above-mentioned human attribute recognition technique recognizes the attribute of a person in an inputted image by finding similar images from a storage device. Therefore, in case few similar images could be found from the storage device, that is, in case the feature space which contains the features of the inputted image is sparse (i.e. a space used to find the similar images is sparse), some dissimilar images will be introduced to use for recognizing the attribute of the person. Especially, since the dimensionality of the features (e.g. Histogram of Oriented Gradient (HOG) features, Local Binary Pattern (LBP) features) which are used for feature matching is high, the feature space which contains the features of the inputted image will become sparser, thus, fewer similar images could be found from the storage device, which will cause more dissimilar images to be introduced to use for recognizing the attribute of the person. Therefore, the accuracy of the similar images will be affected, which will affect the accuracy of the human attribute recognition.

SUMMARY OF THE INVENTION

Therefore, in view of the above recitations in Description of the Related Art, the present disclosure aims to solve at least one point of the issues described above.

According to one aspect of the present disclosure, there is provided a recognition apparatus, comprising: a feature extraction unit configured to extract first features of an object from a region of the object which is obtained from an image; a feature obtainment unit configured to obtain second features of the object at least based on confidence information for first attribute of the object, wherein the confidence information for the first attribute of the object is obtained based on a classifier corresponding to the first attribute and the first features extracted by the feature extraction unit; a sample information determination unit configured to determine sample information from pre-determined sample information based on the second features obtained by the feature obtainment unit; and an attribute recognition unit configured to recognize the first attribute of the object based on the sample information determined by the sample information determination unit.

Wherein, the pre-determined sample information at least comprise labeled first attributes (i.e. Ground Truth (GT) first attributes) and features which are obtained at least based on confidence information for the labeled first attributes.

Wherein, the object is human and the attributes of the object are facial attributes of the human or body attributes of the human. Wherein, the facial attributes of the human are age, gender, race, hair type (e.g. wavy hair, straight hair), hair length (e.g. long hair, short hair), and/or hair color for example. Wherein, the body attributes of the human are body height, body weight, clothes type, clothes pattern, and/or clothes color for example.

Taking advantage of the present disclosure, the accuracy and the speed of the attribute recognition (especially the human attribute recognition) will be improved.

Further characteristic features and advantages of the present disclosure will be apparent from the following description with reference to the drawings.

