Video retrieval method based on deep learning and hash coding

A hash coding and deep learning technology, applied in the field of computer vision, can solve the problems of high computing cost, low efficiency, and long time cost of distance measurement, and achieve the effect of speeding up matching, accurate retrieval results, and reducing storage cost

Active Publication Date: 2017-10-03
INST OF COMPUTING TECH CHINESE ACAD OF SCI
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Problems solved by technology

The main problem with this scheme is that the distance measurement takes a lot of time, especially when the video contains thousands or even tens of thousands of frames of images, this retrieval method will become very inefficien

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  • Video retrieval method based on deep learning and hash coding
  • Video retrieval method based on deep learning and hash coding

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Embodiment Construction

[0031] In order to make the purpose, technical solution and advantages of the present invention more clear, the image retrieval method based on deep learning and hash coding provided in the embodiments of the present invention will be described below with reference to the accompanying drawings.

[0032] Deep learning originated from artificial neural networks. In the field of image or video retrieval, deep learning can combine the underlying features of image or video frame image data to form higher-level representation attribute categories or features to discover distributed feature representations of image or video data, thereby Imitate the human brain mechanism to explain image or video data; hash coding is an algorithm with fast query capability and low memory overhead. In the field of image or video retrieval, image or video content can be expressed as binary by using hash coding hash sequence, and use this sequence to represent the features of the image or video.

[0033...

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Abstract

The invention relates to a network training method for video data on the basis of deep learning and hash coding. The method comprises the following steps: extracting a feature matrix of a video sample by using a deep neural network; carrying out modeling by using the acquired feature matrix of the video sample as a whole body to obtain high-dimensional real value representation of the video sample; and further representing the obtained high-dimensional real value representation into binary hash coding by using a deep network.

Description

technical field [0001] The invention relates to the technical field of computer vision, in particular to a video retrieval method based on deep learning and hash coding. Background technique [0002] With the development of science and technology, the world today has entered the era of big data, especially the rapid growth of video data resources, so the retrieval of large-scale video data to meet user needs has brought new challenges to the field of retrieval technology. A video can be viewed as a collection of continuous still images, that is, a three-dimensional object composed of two-dimensional digital images and a temporal dimension. The problem to be solved for video retrieval is, on the one hand, due to the large scale of the retrieved database, it is necessary to represent the sample data more efficiently to meet the real-time requirements and the constraints of storage overhead; on the other hand, when users use static images to retrieve In the case of video, it i...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06N3/08
CPCG06F16/43G06F16/434G06N3/08
Inventor 陈熙霖乔师师王瑞平
Owner INST OF COMPUTING TECH CHINESE ACAD OF SCI
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