Pedestrian recognition method based on light field camera and HOG and SIFT mixed features

A technology of light field camera and mixed features, which is applied in the field of computer vision and pattern recognition, can solve the problems of increasing the cost of experiments, and cannot solve the problems of false recognition of pedestrian traffic signs, etc., and achieve the effect of simple hardware equipment and high pedestrian recognition rate

Pending Publication Date: 2020-03-06
TIANJIN UNIVERSITY OF TECHNOLOGY
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although these algorithms have obvious advantages, the problem of pedestrian recognition cannot be solved by only using traditional two-dimensional cameras.
[0005] For this problem, we can theo

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
  • Pedestrian recognition method based on light field camera and HOG and SIFT mixed features

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0026] As shown in the figure: a pedestrian recognition method based on light field camera and HOG, SIFT mixed features, including the following steps:

[0027] 1. First, use the LYTRO light field camera to take a large number of pedestrian and non-pedestrian images as positive and negative samples for the experiment.

[0028] 2. Use Lytro Desktop software to obtain the original 2D image and depth map of the captured image;

[0029] 3. Use the method of combining HOG+SIFT mixed features and SVM to extract the ROI area of ​​the original 2D image, filter out the non-pedestrian image with a high probability, and obtain the corresponding pedestrian image; the ROI area extraction of the original 2D image uses the public INRIA data set, using The positive sample is a processed 64*128 size human body image, and the negative sample used is a processed 64*128 size non-human body image;

[0030] 4. Select a certain proportion of positive and negative pedestrian depth image samples for ...

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

A pedestrian identification method based on a light field camera and HOG and SIFT mixed features comprises the following steps: (1) using the light field camera to shoot a large number of pedestrian images as a positive sample of an experiment; (2) shooting a large number of non-pedestrian images by using a light field camera as a negative sample of an experiment; (3) obtaining an original 2D image and a depth map of field of the shot image by using Lytro Desktop software; (4) performing ROI region extraction on the original 2D image by using a method of combining HOG + SIFT mixed features andSVM, and judging whether pedestrians are included or not; and (5) identifying the depth map of the pedestrian judged in the step (4) by using the method of combining the HOG + SIFT mixed features with the SVM again, and judging whether the deceptive pedestrian is included or not. According to the invention, the characteristics that the light field camera can record the scene 4D information and acquire the depth image are utilized to eliminate false identification caused by pedestrian traffic, so that the pedestrian identification capability is enhanced, and the working cost is low.

Description

technical field [0001] The invention belongs to the field of computer vision and pattern recognition, in particular to a pedestrian recognition method based on the mixed features of HOG and SIFT of a light field camera. Background technique [0002] With the development of computer artificial intelligence, many tasks that require a lot of manpower can now be handed over to computers, and computer vision is a recent research hotspot. Computer vision is a discipline that uses cameras and computers to detect and identify targets to obtain the data and information we need. Pedestrian recognition is an important part of the computer vision research field, and it has played a very important role in video surveillance, assisted driving, intelligent human-computer interaction and other fields. [0003] Pedestrian recognition is first and foremost to identify pedestrians. However, in real life, pedestrians are a kind of non-rigid body targets, which are not like vehicles. No matter ...

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
IPC IPC(8): G06K9/00G06K9/46G06K9/32G06K9/62
CPCG06V40/10G06V10/25G06V10/50G06V10/462G06F18/2411
Inventor 石凡贾晨赵萌赵宇峰闫静陈胜勇冯洋博
Owner TIANJIN UNIVERSITY OF TECHNOLOGY
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