Peking University

Jingjia Huang

Ge Li

Nannan Li

Tao Zhang

Jiaxing Zhong

Zhangheng Li

A memory network method based on automatic addressing and recursive information integration. The method is based on a memory neural network framework integrating automatic addressing and recursive information, and is an efficient and lightweight memory network method. A memory is read and written by means of an automatic addressing operation having low time and space complexity, and memory information is effectively utilized by a novel computing unit. The whole framework has the characteristics of high efficiency, high speed and high universality. The method is suitable for various time sequence processing tasks, and shows the performance superior to that of the conventional LSTM and the previous memory network.

Memory network method based on automatic addressing and recursive information integration

Provided is a method for detecting a violent incident in a video based on a hypergraph transition model, comprising a procedure of extracting a foreground target track, a procedure of establishing a hypergraph and a similarity measure, and a procedure of constructing a hypergraph transition descriptor; using the hypergraph to describe a spatial relationship of feature points, in order to reflect attitude information about a movement; and modelling the transition of correlative hypergraphs in a time sequence and extracting a feature descriptor HVC, wherein same can effectively reflect the intensity and stability of the movement. The method firstly analyses the spatial relationship of the feature points and a transition condition of a feature point group, and then performs conjoint analysis on same. The method of the present invention is sensitive to disorderly and irregular behaviours in a video, wherein same is applicable to the detection of violent incidents.

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Shenzhen, China

Jingjia Huang