Face attribute identification method and device and model establishing method

Abstract

The present invention discloses a face attribute identification method and device and a model establishing method, wherein the face attribute identification method comprises the following steps of obtaining a current response area from a current image; according to an average response area and the current response area, calculating an attribute association area; carrying out the area-of-interest pooling on the attribute association area to obtain an undetermined feature graph of a preset size; according to the undetermined feature graph, predicting the face attribute. The face attribute identification method can deform and pool the attribute association area into the undetermined feature graph of the preset size by the area-of-interest pooling, and solves the problem that the scales of the association areas corresponding to the conventional attributes are different, so that a subsequent uniform model-based multi-attribute identification problem is disadvantageous, thereby realizing the face image multi-attribute identification by a convolutional neural network.

Description

technical field [0001] The invention relates to an image recognition technology, in particular to a face attribute recognition method, device and model building method. Background technique [0002] Face attribute recognition refers to the estimation, discrimination and analysis of the attributes shown in the face image. Face attributes include gender, age, expression, movement, whether to wear glasses, whether to wear sunglasses, eye size, eyes open or closed, mouth open or closed, hair length or straight or curly, front or side, etc. It can be seen that the attributes of the face can be divided into long-term attributes and short-term attributes. Long-term attributes refer to attributes that will not change for a period of time, such as gender, age, etc. Short-term attributes refer to attributes attached to the face that can be removed at any time, such as wearing masks, glasses, necklaces, makeup, hairstyles, etc. [0003] At present, the methods of face attribute recog...

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Problems solved by technology

[0008] In order to overcome the deficiencies of the prior art, one of the purposes of the present invention is to provide a face attribute recognition method, which can solve the problem that the existing face attribute recognition method relies on accurate key point positioning of training and test data sets and artificial Define the associated area of ​​the attribute, and it is difficult to learn multiple attributes through a unified model

[0009] The second object of the present invention is to provide a method for establishing a face attribute recognition model, which can solve the problem that existing face attribute recognition methods rely on accurate key point positioning of training and test data sets and manually defined associated regions of attributes. It is difficult to learn multiple attributes through a unified model

[0010] The third object of the present invention is to provide a face attribute recognition device, which can solve the problem that existing face attribute recognition methods rely on accurate key point positioning of training and test data sets and manually defined associated regions of attributes. A unified model to learn multiple attributes is a difficult problem

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