Stereo Vision Based Worker Detection System for Excavator

Obstacle detection is a crucial issue for pilotless device guidance function and it has to be performed with high reliability to avoid any potential collision with the front object. The vision-based obstacle detection systems are regarded perfect for this purpose because they require little on all kind of condition. In this paper, an obstacle detection system using stereo vision sensors and structured light is developed. This system realizes rapid feature matching and high precision measurement distance with the help of structured light, avoiding the time-consuming of the initial corresponding pairs. After the initial detection, the system executes the tracking light strip algorithm for the obstacles. The proposed system can detect a front obstacle in vision field and obtain the size of obstacle. The proposed obstacle detection system is set up and its performance is verified experimentally

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Research on intrusion clearance detection system for high-speed railway based on binocular stereo vision

Proceedings of 2011 IEEE International Conference on Service Operations, Logistics and Informatics ◽

10.1109/soli.2011.5986618 ◽

2011 ◽

Cited By ~ 1

Author(s):

Zujun Yu ◽

Xi He

Keyword(s):

Stereo Vision ◽

High Speed ◽

Detection System ◽

High Speed Railway ◽

Binocular Stereo Vision ◽

Binocular Stereo

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Real-time stereo vision-based lane detection system

Measurement Science and Technology ◽

10.1088/1361-6501/aac163 ◽

2018 ◽

Vol 29 (7) ◽

pp. 074005 ◽

Cited By ~ 16

Author(s):

Rui Fan ◽

Naim Dahnoun

Keyword(s):

Real Time ◽

Stereo Vision ◽

Detection System ◽

Lane Detection

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Stereo Vision-Based Road Debris Detection System for Advanced Driver Assistance Systems

SAE International Journal of Transportation Safety ◽

10.4271/09-10-01-0003 ◽

2021 ◽

Vol 10 (1) ◽

Author(s):

Naveen Kumar Bangalore Ramaiah ◽

◽

Subrata Kumar Kundu ◽

Keyword(s):

Stereo Vision ◽

Detection System ◽

Autonomous Vehicle ◽

Warning System ◽

Detection Algorithm ◽

Potential Threat ◽

Safe Driving ◽

Collision Warning ◽

On The Road ◽

3D Information

Reliable detection of obstacles around an autonomous vehicle is essential to avoid potential collision and ensure safe driving. However, a vast majority of existing systems are mainly focused on detecting large obstacles such as vehicles, pedestrians, and so on. Detection of small obstacles such as road debris, which pose a serious potential threat are often overlooked. In this article, a novel stereo vision-based road debris detection algorithm is proposed that detects debris on the road surfaces and estimates their height accurately. Moreover, a collision warning system that could warn the driver of an imminent crash by using 3D information of detected debris has been studied. A novel feature-based classifier that uses a combination of strong and weak features has been developed for the proposed algorithm, which identifies debris from selected candidates and calculates its height. 3D information of detected debris and vehicle’s speed are used in the collision warning system to warn the driver to safely maneuver the vehicle. The performance of the proposed algorithm has been evaluated by implementing it on a passenger vehicle. Experimental results confirm that the proposed algorithm can successfully detect debris of ≥5 cm height for up to a 22 m distance with an accuracy of 90%. Moreover, the debris detection algorithm runs at 20 Hz in a commercially available stereo camera making it suitable for real-time applications in commercial vehicles.

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