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Space-time behavior detection method

一种检测方法、时空的技术,应用在计算机视觉领域,能够解决时空行为检测方法鲁棒性差、无法有效结合执行者等问题,达到有利于帧级定位、减少行为搜索空间、检测效率提升的效果

Inactive Publication Date: 2019-07-02
HUAZHONG UNIV OF SCI & TECH
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  • Claims
  • Application Information

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Problems solved by technology

[0005] Aiming at the defects of the prior art, the purpose of the present invention is to provide a spatio-temporal behavior detection method, which aims to solve the weak supervised spatio-temporal behavior detection method caused by the inability of the prior art to effectively combine executors, specific motion information and temporal recognition behaviors. The problem of poor robustness

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Embodiment Construction

[0074] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0075] Such as figure 1 As shown, the present invention provides a spatio-temporal behavior detection method based on weak supervision, including:

[0076] (1) Object detection is performed on all frames in the sample video to obtain a set of candidate objects;

[0077] (2) Calculate the optical flow information between all frames in the sample video to obtain the motion set;

[0078] (3) Based on the candidate object set and motion set, construct a spatio-temporal convolution-deconvolution network with additional object attention mechanism and motion attention mechanism;

[0079] (4) Taking the...

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Abstract

The invention discloses a space-time behavior detection method, which comprises the following steps: carrying out object detection on all frames in a sample video to obtain a candidate object set; calculating all inter-frame optical flow information in the sample video, and obtaining a motion set; constructing a space-time convolution-deconvolution network for constructing additional object attention mechanism and motion attention mechanism; after performing space-time convolution processing on each time slice of the sample video, adding corresponding sparse variables and sparse constraints toobtain a network structure S; training the network structure S by taking the classification loss based on the cross entropy and the loss of the sparse constraint as objective functions; and calculating behavior types and sparse coefficients corresponding to the time slices in the test sample video, and obtaining an object behavior space-time position. According to the method, through object detection and optical flow prediction, the behavior search space is reduced, and space-time behavior detection has good robustness.

Description

technical field [0001] The invention belongs to the field of computer vision, and more specifically relates to a spatiotemporal behavior detection method. Background technique [0002] Behavior analysis is an important and active research hotspot in current computer vision. It not only has a wide range of applications in the field of social security, such as abnormal behavior detection in the monitoring environment, detection and recognition of theft in shopping malls, but also plays an important role in human-computer interaction. For example, service robots can effectively predict the behavior of the elderly to prevent accidents. In addition, they can also be used to detect and identify pornographic, reactionary, and violent behaviors such as existing social networks and live broadcast platforms. [0003] The current behavior detection methods are divided into two categories from the required supervision information: one is a method based on strong supervision, and its sup...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06V10/774
CPCG06V20/42G06F18/214G06V20/49G06V20/41G06V2201/07G06V10/82G06V10/774G06T7/207G06T7/215G06T3/4053G06T2207/10016G06T2207/20072G06T2207/20076G06T2207/20164G06T3/16
Inventor 桑农张士伟李致远高常鑫邵远杰
Owner HUAZHONG UNIV OF SCI & TECH
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