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Human-like concept learning method and device for video events

A technology for video event and concept learning, which is applied to computer components, instruments, calculations, etc., and can solve problems such as inability to learn video event concepts

Active Publication Date: 2017-08-08
SHENZHEN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The main purpose of the present invention is to provide a method and device for learning human-like concepts of video events, aiming to solve the technical problem in the prior art that the concept of video events cannot be learned like a human

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  • Human-like concept learning method and device for video events
  • Human-like concept learning method and device for video events

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Embodiment Construction

[0025] In order to make the purpose, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described The embodiments are only some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative efforts belong to the protection scope of the present invention.

[0026] The technical scheme in the embodiment of the present invention introduces the Bayesian Program Learning (BPL) framework, which can learn a large class of video event concepts from only one video sample, and the concepts are expressed as simple probability programming, that is, Probabilistic generative models expressed by structured pr...

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Abstract

The invention discloses a human-like concept learning method and a device for video events. The method comprises the following steps: dividing moving objects in a video sample through a random walk algorithm to get a behavior set; dividing the behaviors in the behavior set based on the time points of pause of behaviors to get a sub-behavior set; determining the time-space relationship between each sub-behavior and the other sub-behaviors and the prior probability of the time-space relationship of each sub-behavior in the sub-behavior set; and combining the time-space relationship between the sub-behaviors, the prior probability of each sub-behavior and a preset change factor set into a new video event, and learning the concept of the video event. Compared with the prior art, the concept of a video event can be learned through the method, the concept is expressed through simple and random planning, a thinking of concept learning close to human beings is realized, and human-like video event concept learning is realized.

Description

technical field [0001] The invention relates to the field of video image processing, in particular to a method and device for learning human-like concepts of video events. Background technique [0002] Humans' learning of new concepts can generalize from a single example, whereas machine learning algorithms typically require a large number of samples to achieve the same accuracy. For example, current video-based behavior analysis and concept learning both require a large number of videos as samples and can only be realized after complex machine learning algorithms, while humans can learn the same number or even more concepts from a single video sample. [0003] Therefore, how to learn the concept of video events like humans is the focus of current research. Contents of the invention [0004] The main purpose of the present invention is to provide a method and device for learning human-like concepts of video events, aiming at solving the technical problem in the prior art ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/42G06F18/214G06F18/2415
Inventor 李岩山徐健杰李泓毅谢维信
Owner SHENZHEN UNIV