Image set classification method based on aggregation hash learning

Abstract

The invention discloses an image set classification method based on aggregation hash learning, and the method comprises the following steps: S1, building a hash aggregation model according to a training image set; s2, training the Hash aggregation model to obtain a trained linear Hash function and an instance Hash code matrix of a training image set; s3, according to the trained linear hash function, calculating a hash code of an instance of the to-be-classified image set; s4, obtaining the category of the to-be-classified image set according to the distance between the hash code of the instance of the to-be-classified image set and the instance hash code matrix of the training image set; the method solves the problems that the existing hash learning method does not well consider the set information of the image set, it is difficult to keep the similarity of examples in the Hamming space, it is difficult to obtain high-quality example hash codes, and then the classification precision of the image set is affected.

Description

technical field [0001] The invention relates to the technical field of image classification, in particular to an image set classification method based on aggregated hash learning. Background technique [0002] Over the years, with the rapid development of multimedia technology, image set classification has been widely used in a large number of real-world applications, such as object classification, video-based face recognition. Compared with traditional single-shot image-based classification tasks, image set classification pays more attention to the generality of the set and the complementarity of samples, which can provide richer information to describe the corresponding topics. The interest in image set classification has been steadily growing in the research community as image set classification can provide more promising performance to overcome the appearance variations of images (e.g. appearance, occlusion, lighting, expression, pose). However, how to deal with extreme...

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Problems solved by technology

[0004] Aiming at the above-mentioned deficiencies in the prior art, the present invention provides an image set classification method based on aggregated hash learning to solve the problem that the existing hash learning method does not consider the set information of the image set well, and it is difficult to Hamming space maintains the similarity of instances, and it is difficult to obtain high-quality instance hash codes, which in turn affects the classification accuracy of image sets

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