Human body motion recognition method based on mixed descriptor
A hybrid descriptor and human motion technology, applied in the field of image processing, to achieve the effect of low dimension, reducing the amount of data calculation, and increasing detailed information
Active Publication Date: 2013-07-03
青岛华师智慧科技有限公司
View PDF5 Cites 22 Cited by
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
[0007] The purpose of the present invention is to address the shortcomings of the above-mentioned prior art, and propose a human body behavior recognition method based on a hybrid descriptor, which reduces the complexity of human body feature extraction from the structural characteristics of the human body and the motion characteristics of the human body, and does not require a large amount of training data. effectively improve the accuracy of human motion recognition
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 moreImage
Smart Image Click on the blue labels to locate them in the text.
Smart ImageViewing Examples
Examples
Experimental program
Comparison scheme
Effect test
Embodiment Construction
[0035] refer to figure 1 , the specific implementation steps of the present invention are as follows:
[0036] Step 1, obtain the training video set X and test video set T of the entire human body motion recognition.
[0037] (1.1) Construct a training video set X and a test video set T from the sports videos in the Weizmann database according to the ratio of 8:1; where, the download address of the Weizmann database is http: / / www.wisdom.weizmann.ac.il / ~vision / SpaceTimeActions.html , figure 2 Sequence images of some videos in the database are given;
[0038] (1.2) Convert each video in the training video set X and the test video set T into a continuous single sequence of images.
[0039] Step 2: Use the frame difference method to perform background subtraction on a single sequence image in the training video set X, and convert the color image after background subtraction into a binary image.
[0040] The described color image after the background subtraction is changed in...
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
Login to View More Abstract
The invention provides a human body motion recognition method based on a mixed descriptor and mainly solves the problems that feature extraction is complex and representational capacity is low in the prior art. The human body motion recognition method based on the mixed descriptor comprises the following steps of: (1) obtaining video data of human motion, and constructing a training video set X and a test video set T according to the ratio of 8:1; (2) extracting five vertex coordinates of a human body star-shaped model in each video and calculating polar radiuses and polar angles of the five vertex coordinates in an independent coordinate system to obtain characteristics of a statistical histogram of each part of a human body; (4) extracting motion characteristics of all the images in one video; (5) cascading the characteristics of the statistical histogram with the motion characteristics to form final characteristics of the video; and (6) respectively extracting characteristics of all the videos in the training video set X and the test video set T to obtain a training video characteristic set X* and a test video characteristic set T*, and learning and training the training video characteristic set X* and the test video characteristic set T* to obtain classification results. The human body motion recognition method based on a mixed descriptor can accurately recognize the human motion and can be used for video processing such as video monitoring, target recognition and motion recognition.
Description
technical field [0001] The invention belongs to the technical field of image processing, relates to a human motion recognition method, and can be used for virtual video, intelligent monitoring and attitude estimation. Background technique [0002] Human motion recognition is one of the major hotspots in the field of computer vision in recent years. Human motion recognition has been initially applied in many fields such as motion capture, human-computer interaction, and video surveillance, and has great application prospects. Due to the variability and diversity of human motion, noisy background, lighting conditions, clothing texture and self-occlusion and other factors seriously affect the recognition effect of human motion, it is important to accurately estimate human body posture from video images and realize human motion recognition. A long-standing problem in computer vision. [0003] At present, the methods of human motion recognition are mainly divided into three cate...
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
Login to View More IPC IPC(8): G06K9/00G06K9/62
Inventor 韩红焦李成王爽李晓君张红蕾谢福强韩启强顾建银
Owner 青岛华师智慧科技有限公司