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Visual sense mapping method based on support vector regression

A technology that supports vector regression and mapping methods, which can be applied to instruments, character and pattern recognition, computer components, etc., and can solve problems such as poor visual mapping estimation results

Active Publication Date: 2017-05-17
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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Problems solved by technology

This invention patent solves the problem of poor estimation effect of existing visual mapping methods in the case of a small number of training samples

Method used

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  • Visual sense mapping method based on support vector regression
  • Visual sense mapping method based on support vector regression
  • Visual sense mapping method based on support vector regression

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[0046] Implementation language: Matlab, C / C++

[0047] Hardware platform: Intel core2 E7400+4G DDR RAM

[0048] Software platform: Matlab2012a, VisualStdio2010

[0049] According to the method of the present invention, first clearly the visual mapping problem to be solved, and collect relevant images (head image, body image and facial image, etc.) and calibrate the target value (head posture angle, body posture angle and age). According to the patent of the present invention, first use Matlab or C language to write a program to learn the support vector regression model from the image to the target value; then visually map the input image to be estimated to estimate the target value. The method of the invention can be used for visual mapping problems in various computer visions, and can solve the problem of limited training samples in practical applications.

[0050] A visual mapping method based on support vector regression:

[0051] Step 1: Collect N input images according...

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Abstract

The invention discloses a visual sense mapping method based on support vector regression. The visual sense mapping method is such a method as to estimate the corresponding continuous target values from the inputted image characteristics, for instance, the altitude estimation, age estimation and visual line tracking, etc. In the practical application, one widely existing problem faced in the training of a mapping model is that the number of training samples is limited. The visual sense mapping method based on support vector regression proposed by the invention can overcome the above problem effectively. When given a new sample, the method directly utilizes the learned linear regression function with kernel function to predict the target values. The training time of the method is short and the operation is convenient and simple.

Description

technical field [0001] The invention belongs to the technical field of computer vision, relates to visual mapping technology, and is mainly used in visual problems such as posture estimation, line of sight tracking, age estimation and body posture estimation. Background technique [0002] In computer vision, visual mapping refers to the process of learning a mapping function between input image features and output variables, so that when a new image is input, the target output value corresponding to the input image is estimated. Specifically, visual mapping includes: human body pose estimation, head pose estimation, line of sight estimation, and object tracking. See references for details: O.Williams, A.Blake, and R.Cipolla, Sparse and Semi-Supervised Visual Mapping with the S3GP, in IEEEConference Computer on Computer Vision and Pattern Recognition, pp.230-237, 2006. [0003] As an important branch of computer vision, visual mapping has changed the situation where humans e...

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Application Information

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IPC IPC(8): G06K9/62
CPCG06V10/758G06F18/213G06F18/2411
Inventor 潘力立
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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