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Efficient motion characterization method and device based on motion boundary small displacement

A motion boundary, small displacement technology, applied in the fields of visual perception and artificial intelligence, can solve the problems of time-consuming and high computational complexity, and achieve the effect of ensuring real-time performance, high computational complexity, and small number of parameters

Pending Publication Date: 2021-03-05
PEKING UNIV SHENZHEN GRADUATE SCHOOL
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Problems solved by technology

[0005] Aiming at the problems that the current mainstream video understanding methods rely heavily on optical flow as motion representation, the calculation complexity is high and time-consuming, the present invention proposes an efficient motion representation method and device based on small displacement of motion boundary

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  • Efficient motion characterization method and device based on motion boundary small displacement
  • Efficient motion characterization method and device based on motion boundary small displacement
  • Efficient motion characterization method and device based on motion boundary small displacement

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Embodiment Construction

[0040] Below in conjunction with accompanying drawing, further describe the present invention through embodiment, but do not limit the scope of the present invention in any way.

[0041] figure 1 In order to show an overall flow chart of an efficient motion characterization method based on small motion boundary displacement according to an example, it specifically includes the following steps:

[0042] Step 1: Adjacent sampling S1, extracting the original image of adjacent N frames in the video sequence; the adjacent N frames are N image frames adjacent in temporal relationship, and N is preset to be greater than or equal to 2 is an integer, then a video sequence extracts the original image of adjacent N frames as a sampling frame;

[0043] Step 2: Convolutional neural network shallow layer processing S2, using the convolutional neural network to process the original image of the adjacent N frames to obtain the corresponding shallow feature map; the convolutional neural netwo...

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Abstract

The invention relates to an efficient motion characterization method and device based on motion boundary small displacement. The method comprises the following steps: step 1, extracting original images of adjacent N frames in a video sequence; 2, processing adjacent N frames of original images by using a convolutional neural network to obtain a corresponding shallow feature map; 3, performing difference calculation on the shallow feature maps of all the two adjacent frames of the adjacent N frames to obtain a difference map of all the two adjacent frames in the feature space; 4, carrying out difference accumulation on difference graphs of all two adjacent frames in the feature space along the channel dimension; and step 5, encoding the difference accumulation result according to an encoding scheme so as to obtain the efficient motion representation provided by the invention. Compared with some methods depending on optical flow as motion characterization, the method does not need to perform complex optical flow calculation in advance, and can model the small displacement of the motion boundary by calculating the difference on the shallow feature space, thereby greatly reducing the complexity of motion characterization calculation.

Description

technical field [0001] The present invention relates to visual perception and artificial intelligence technology, in particular to an efficient motion characterization method and device based on small motion boundary displacements, which can effectively construct A small displacement of the mode motion boundary is used as a motion characterization. Background technique [0002] Motion representations have been widely adopted in computer vision research in recent years, especially for video understanding tasks. The current mainstream video-based deep learning tasks, such as: action recognition, video description, video prediction, etc., in addition to the original color 3-channel RGB image as input to provide appearance information, motion representation is also required as one of the input modalities. To provide timing-related short-range motion information as a learning aid. The modeling of motion representations has gradually become an important research direction in the...

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Application Information

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IPC IPC(8): G06K9/00G06N3/04
CPCG06V20/42G06V20/46G06N3/045
Inventor 邹月娴张粲
Owner PEKING UNIV SHENZHEN GRADUATE SCHOOL
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