Video action quality evaluation method and system based on group-sensitive contrastive regression

A quality evaluation and video technology, applied in the field of computer vision and deep learning, can solve the problems of difficult score prediction and small video differences in subjective evaluation of judges, so as to improve interpretability and evaluation ability, and improve the accuracy of action quality evaluation Effect

Active Publication Date: 2021-12-24
TSINGHUA UNIV
View PDF5 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Despite some promising results, AQA still faces two challenges: first, since score labels are usually annotated by human judges (e.g., scores for diving competitions are calculated by aggregating scores from different Accurate score prediction is difficult for subjective evaluation; second, the variance between videos used for the AQA task is very small because actors usually perform the same actions in similar environments

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Video action quality evaluation method and system based on group-sensitive contrastive regression
  • Video action quality evaluation method and system based on group-sensitive contrastive regression
  • Video action quality evaluation method and system based on group-sensitive contrastive regression

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0025] Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals designate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary and are intended to explain the present invention and should not be construed as limiting the present invention.

[0026] The present invention remodels the AQA problem as regressing difference scores with reference to other videos with the same attributes (such as videos of the same type of motion or with the same difficulty level), instead of directly learning to predict unknown scores. By introducing examples for rating prediction, the regressor will refer to known ratings given by human referees and be encouraged to predict the current video rating based on the slight differences between the current video and the examples.

[0027] The vi...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a video action quality evaluation method and system based on group-sensitive contrastive regression, wherein the method includes: selecting a corresponding example video and example video score according to the current video; Perform spatio-temporal feature extraction and construct merged features; build a group-sensitive regression tree network to regress the merged features to get the final difference score, and combine the final difference score with the sample video score to get the current video score. This method obtains the final target action score by modeling the gap between the target action and the example action, which improves the accuracy of the model's action quality evaluation.

Description

technical field [0001] The invention relates to the technical fields of computer vision and deep learning, in particular to a method and system for evaluating video action quality based on group-sensitive contrastive regression. Background technique [0002] Video Action Quality Assessment (AQA), which aims to evaluate the performance of a specific action, has received increasing attention in recent years because of its crucial role in many real-world applications, including sports and healthcare. important role. Different from conventional action analysis tasks such as action detection and recognition, AQA is more challenging because it needs to predict fine-grained scores from videos containing actions of the same category. Considering the differences between different videos themselves and their action scores, we believe that the key to solving this problem is to discover the differences between videos and predict the scores based on the differences. [0003] In recent ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Patents(China)
IPC IPC(8): H04N17/00
CPCH04N17/00
Inventor 鲁继文周杰饶永铭于旭敏
Owner TSINGHUA UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap