The recognition and tracking of traffic lights based on color segmentation and CAMSHIFT for intelligent vehicles

Gong, Jianya; Jiang, Yanhua; Xiong, Guangming; Guan, Chao-Hua; Tao, Gang; Chen, Huiyan

doi:10.1109/ivs.2010.5548083

Cited by 119 publications

(49 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Jianwei Gong et al [14] present colour-based segmentation method with CAMShift tracking algorithm for detection and tracking of traffic lights using a camera that is mounted on a moving vehicle. Donghe and Jinson [5] integrate a filtering prediction with a CAMShift tracking algorithm to improve object tracking against occlusion.…”

Section: Related Workmentioning

confidence: 99%

A Robust Visual Object Tracking Approach on a Mobile Device

Mohammed

Morris

2014

Information and Communication Technology

View full text Add to dashboard Cite

Abstract. In this paper, we present an approach for tracking an object in video captured on a mobile device. We use a colour-based approach. The performance of many of these approaches degrades due to lighting changes and occlusion. To address the issue of lightning changes, our approach makes use of colour histogram that is generated by accumulating histograms derived from target objects imaged under different conditions. A CAMShift tracking algorithm is applied to the back-projected image to track the target object.We have tested our approach by tracking an Emergency Exit sign and the results obtained show that the tracking is robust against lightning changes.

show abstract

Section: Related Workmentioning

confidence: 99%

A Robust Visual Object Tracking Approach on a Mobile Device

Mohammed

Morris

2014

Information and Communication Technology

View full text Add to dashboard Cite

show abstract

“…In the SC area, our previous works can get enough information, including detections of lane markings [22], traffic lights [23] and signs [24], to provide the direction and the speed limit for the UGV. Because the GPS signal only provides global path information, the GPS receiver used in our UGV can be just an ordinary one with low positioning accuracy.…”

Section: Hybrid Map-based Navigationmentioning

confidence: 99%

Hybrid Map-Based Navigation Method for Unmanned Ground Vehicle in Urban Scenario

Gong

Jiang

et al. 2013

Remote Sensing

Self Cite

View full text Add to dashboard Cite

Abstract:To reduce the data size of metric map and map matching computational cost in unmanned ground vehicle self-driving navigation in urban scenarios, a metric-topological hybrid map navigation system is proposed in this paper. According to the different positioning accuracy requirements, urban areas are divided into strong constraint (SC) areas, such as roads with lanes, and loose constraint (LC) areas, such as intersections and open areas. As direction of the self-driving vehicle is provided by traffic lanes and global waypoints in the road network, a simple topological map is fit for the navigation in the SC areas. While in the LC areas, the navigation of the self-driving vehicle mainly relies on the positioning information. Simultaneous localization and mapping technology is used to provide a detailed metric map in the LC areas, and a window constraint Markov localization algorithm is introduced to achieve accurate position using laser scanner. Furthermore, the real-time performance of the Markov algorithm is enhanced by using a constraint window to restrict the size of the state space. By registering the metric maps into the road network, a hybrid map of the urban scenario can be constructed. Real unmanned vehicle mapping and navigation tests demonstrated the capabilities of the proposed method.

show abstract

“…After that, we can use the template matching algorithm or machine learning algorithm to recognize the traffic light. In this paper, we just use the algorithm described in [9] to complete the recognition and the result is shown in Figure 4.…”

Section: Traffic Light Recognitionmentioning

confidence: 99%