Vision-Based Real-Time Lane Marking Detection and Tracking

Liu, Wei; Zhang, Hongliang; Duan, Bobo; Yuan, Huai; Zhao, Hong

doi:10.1109/itsc.2008.4732527

Cited by 46 publications

(24 citation statements)

References 6 publications

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“…We first compared our model with the global model, which is widely used in many state-of-art systems [9], [12], [14]. The state vector for our global model was [a, b, c l , c r ].…”

Section: Resultsmentioning

confidence: 99%

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A global and local condensation for lane tracking

Yao

Deng

Chen

2012

2012 15th International IEEE Conference on Intelligent Transportation Systems

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In this paper, we present a new condensation filtering algorithm that combines local and global information for tracking of lane markings. Local model is used for condensation particle filtering while global one for resampling of local filters and vehicle control command. The detection and tracking process is done based on bird's-eye images in real-time. Unlike most of the state-of-art systems, in our system, with the help of a 3D lidar mounted on the vehicle, the computation of bird's-eye image and the dynamic pitch estimation could be readily and accurately accomplished through joint calibration of camera and 3D lidar. In addition, multiple image features are fused to weight particles. The experimental results on various road environments demonstrate the robustness of our approach.

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“…We first compared our model with the global model, which is widely used in many state-of-art systems [9], [12], [14]. The state vector for our global model was [a, b, c l , c r ].…”

Section: Resultsmentioning

confidence: 99%

“…Many representative systems have been developed. Some of them keep track of lane markings on original images [8]- [10] while others use bird's-eye images [11], [12], or combines them together [13], [14]. Distance transform is an effective way in measuring weights for the particles [8], [9], [11].…”

Section: Introductionmentioning

confidence: 99%

A global and local condensation for lane tracking

Yao

Deng

Chen

2012

2012 15th International IEEE Conference on Intelligent Transportation Systems

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show abstract

“…차선 검 출을 위해서 레이더나 레이저 스캐너와 같은 센서를 사용하기 도 하지만 비전센서를 이용하여 검출하는 것이 보다 일반적이 다. LDWS시스템에서 차선 검출을 위해 사용된 기존의 방법 들에는 에지(edge) 정보를 이용하는 방법 [4,5]과 컬러모델을 이용하는 방법 [6], B-Snake를 이용하는 방법 [7], 그리고 Perspective 변환을 이용하는 방법 [8] …”

Section: 에 보다 많은 연구가 진행되고 있다unclassified

Model-based Curved Lane Detection using Geometric Relation between Camera and Road Plane

장호진¹,

백승해²,

박순용³

2015

Journal of Institute of Control, Robotics and Systems

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Abstract:In this paper, we propose a robust curved lane marking detection method. Several lane detection methods have been proposed, however most of them have considered only straight lanes. Compared to the number of straight lane detection researches, less number of curved-lane detection researches has been investigated. This paper proposes a new curved lane detection and tracking method which is robust to various illumination conditions. First, the proposed methods detect straight lanes using a robust road feature image. Using the geometric relation between a vehicle camera and the road plane, several circle models are generated, which are later projected as curved lane models on the camera images. On the top of the detected straight lanes, the curved lane models are superimposed to match with the road feature image. Then, each curve model is voted based on the distribution of road features.

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“…The recognition and extraction of road markings have been seen as important functions in many fields, such as traffic safety management [2,3], driver assistance [4][5][6], and intelligent transportation [7,8]. Traditional studies have mostly focused on digital images and videos [9][10][11][12][13][14][15]. The extraction results are sometimes incomplete or insufficient due to poor weather conditions, lighting conditions, and complex shadowing from trees.…”

Section: Introductionmentioning

confidence: 99%

Recognition and Reconstruction of Zebra Crossings on Roads from Mobile Laser Scanning Data

Zhang

Ying

et al. 2016

IJGI

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Zebra crossings provide guidance and warning to pedestrians and drivers, thereby playing an important role in traffic safety management. Most previous studies have focused on detecting zebra stripes but have not provided full information about the areas, which is critical to both driver assistance systems and guide systems for blind individuals. This paper presents a stepwise procedure for recognizing and reconstructing zebra crossings using mobile laser scanning data. First, we propose adaptive thresholding based on road surface partitioning to reduce the impact of intensity unevenness and improve the accuracy of road marking extraction. Then, dispersion degree filtering is used to reduce the noise. Finally, zebra stripes are recognized according to the rectangular feature and fixed size, which is followed by area reconstruction according to arrangement patterns. We test our method on three datasets captured by an Optech Lynx mobile mapping system. The total recognition rate of 90.91% demonstrates the effectiveness of the method.

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Vision-Based Real-Time Lane Marking Detection and Tracking

Cited by 46 publications

References 6 publications

A global and local condensation for lane tracking

A global and local condensation for lane tracking

Model-based Curved Lane Detection using Geometric Relation between Camera and Road Plane

Recognition and Reconstruction of Zebra Crossings on Roads from Mobile Laser Scanning Data

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