A 3D road vehicle tracking method

A road vehicle, 3D technology, applied in the field of computer vision, can solve complex motion modeling, target occlusion and other problems

Active Publication Date: 2019-01-29
UNIV OF ELECTRONICS SCI & TECH OF CHINA
View PDF6 Cites 9 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in the face of the complex traffic environment in the city, the above methods still have certain deficiencies in solving problems such as object occlusion, complex motion modeling, and trade-off between computational complexity and computational accuracy.

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
  • A 3D road vehicle tracking method
  • A 3D road vehicle tracking method
  • A 3D road vehicle tracking method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0153] In order to further illustrate the tracking processing performance of the present invention, the tracking method of the present invention is compared with the existing MDP tracking algorithm for two kinds of scenes (mutual occlusion scene, similar target appearance scene), as follows Figure 5 As shown, it can be seen from the figure that when there are complex road conditions such as occlusion and similar appearance of the target, the improved tracking method of the present invention can still effectively track the target, which is greatly improved compared with the existing tracking algorithm, namely The performance of the invention is obviously better than the existing MDP tracking algorithm.

[0154] The tracking method of the present invention combines the detection set of 2D-3D features of the target, and can use the Fast R-CNN target detection network and 3DOP algorithm to obtain detection processing results; the present invention combines the target 3D spatial fe...

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 3D road vehicle tracking method. The invention belongs to the technical field of computational vision processing. A 3D spatial feature and 2D image feature of an object are combined with an MDP model. The evaluation function is reconstructed, and a multi-target tracking method based on 2D and 3D joint features is proposed. The original 2D image domain tracking is extendedto 3D spatial domain tracking, which effectively solves the technical problems such as mistracking and drift when vehicles with similar appearance and close distance occlude each other.

Description

technical field [0001] The invention belongs to the technical field of computer vision, and in particular relates to a 3D multi-target tracking method based on image color and depth information. Background technique [0002] With the vigorous development of artificial intelligence technology, smart cars with (Advanced Driver Assistance System, referred to as ADAS) and unmanned driving technology as the core have become the development direction of future cars. As one of its key technologies, multi-target tracking and detection has always been It is a research hotspot in this field. [0003] At present, most target tracking and detection algorithms focus on RGB images, such as the famous TLD (Tracking-Learning-Detection) algorithm proposed by Kalal et al., which integrates detection, learning and tracking. Single target tracking algorithm. Fast RCNN, Faster RCNN, YOLO, etc. proposed by Girshick successively, these algorithms are relatively successful target detection algori...

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 Applications(China)
IPC IPC(8): G06T7/246G06K9/62
CPCG06T7/246G06T2207/30241G06T2207/10016G06T2207/20081G06F18/22G06F18/2411
Inventor 王正宁吕侠张翔周阳曾凡伟何庆东
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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