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Human movement detection method based on movement dictionary learning

A technology of human action and dictionary learning, applied in the field of computer vision

Active Publication Date: 2014-12-10
HOPE CLEAN ENERGY (GRP) CO LTD
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  • Abstract
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  • Claims
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Problems solved by technology

There have also been attempts to use spatio-temporal patches to replace body parts, but the criteria for choosing spatio-temporal patches and how many spatio-temporal patches are needed to capture all possible variations in human motion have not yet been resolved

Method used

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  • Human movement detection method based on movement dictionary learning
  • Human movement detection method based on movement dictionary learning
  • Human movement detection method based on movement dictionary learning

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Embodiment Construction

[0034] In order to describe the content of the embodiment conveniently, some terms are defined first.

[0035] Definition 1: Local Trinary Patterns (LTP). It is a local feature representation method and an extension of Local Binary Patterns (LBP) in the space-time domain. It effectively captures motion information by inter-frame encoding of moving image sequences, thereby avoiding any complex calculation of optical flow. The process can be regarded as a spatiotemporal local texture description algorithm. A one-dimensional feature vector can be obtained by extracting LTP features containing certain human action video clips. The local feature representation method has the advantages of strong discrimination ability and fast calculation speed. See literature for details: Yeffet L, Wolf L. Local trinary patterns for human action recognition [C] / / Computer Vision, International Conference on. IEEE, 2009:492-497.

[0036] Definition 2: Random projection. It is a dimensionality re...

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Abstract

The invention discloses a human movement detection method based on movement dictionary learning. The human movement detection method includes that at the training stage, using a local property representing method to extract human movement properties from different video clips, and learning a human movement dictionary with strong distinguishing ability through training; considering reconstructing errors and new errors when modeling the movement dictionary so as to model better; at the testing stage, enabling a space-time sliding window to traverse the sparse codes of sliding windows of the whole video, and judging whether the space-time sliding window comprises a human movement according to the response values of the sparse codes to different dictionary items. The human movement detection method based on the movement dictionary learning can obtain the human movement dictionary through training without a negative sample, and the training process is easy and quick to finish.

Description

technical field [0001] The invention belongs to computer vision technology and relates to human body motion detection technology. Background technique [0002] Human activity analysis is one of the most active research topics in the field of computer vision. Its core is to use computer vision technology to detect, track and recognize people from image sequences and understand and describe their behavior. The human motion detection method based on computer vision is the core technology of human motion analysis research, which includes detecting the human body in the field of view and obtaining parameters reflecting human motion to achieve the purpose of understanding human motion; in intelligent monitoring, smart home appliances, Human-computer interaction, content-based video retrieval and image compression have broad application prospects and great economic and social value. In practical applications, human motion detection is extremely difficult due to adverse factors suc...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
Inventor 解梅蔡勇何磊蔡家柱
Owner HOPE CLEAN ENERGY (GRP) CO LTD
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