Real-time recognition of U.S. speed signs

Keller, Christoph G.; Sprunk, Christoph; Bahlmann, Claus; Giebel, J.; Baratoff, Gregory

doi:10.1109/ivs.2008.4621282

Cited by 80 publications

(40 citation statements)

References 20 publications

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“…Examples are detection of buildings in remotely sensed images [24,19,14,3,12,15,1,31,30,23,26], traffic signs [21,13,22], and particles of a rectangular shape in cryo-electron microscopy images [36,35]. The methods used were based on Markov Random Fields [15,21], Marked Point Processes [1,26], search on a graph [14,38], Hough Transform and other voting schemes [3,12,36,13,22], template matching [25], aggregation of local features [1,23,31], and heuristic rules [19].…”

Section: Related Workmentioning

confidence: 99%

Detection of incomplete enclosures of rectangular shape in remotely sensed images

Zingman

Saupe

Lambers

2015

2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

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Section: Related Workmentioning

confidence: 99%

Detection of incomplete enclosures of rectangular shape in remotely sensed images

Zingman

Saupe

Lambers

2015

2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

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“…However, the learningbased methods have taken over lately, since they cope better with real-world variations in the input data. They use a wealth of features, such as Haar-wavelets [14], HOG [15], or Integral Channel Features [9].…”

Section: Related Workmentioning

confidence: 99%

“…It shows promising detection results in the 90%-range, albeit with several false positives per image, much higher than what would be acceptable in a production system. Older contributions include [14], [23], [24].…”

Section: Related Workmentioning

confidence: 99%

Traffic sign detection for U.S. roads: Remaining challenges and a case for tracking

Møgelmose

Liu

Trivedi

2014

17th International IEEE Conference on Intelligent Transportation Systems (ITSC)

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Abstract-Traffic sign detection is crucial in intelligent vehicles, no matter if one's objective is to develop Advanced Driver Assistance Systems or autonomous cars. Recent advances in traffic sign detection, especially the great effort put into the competition German Traffic Sign Detection Benchmark, have given rise to very reliable detection systems when tested on European signs. The U.S., however, has a rather different approach to traffic sign design. This paper evaluates whether a current state-of-the-art traffic sign detector is useful for American signs. We find that for colorful, distinctively shaped signs, Integral Channel Features work well, but it fails on the large superclass of speed limit signs and similar designs.We also introduce an extension to the largest public dataset of American signs, the LISA Traffic Sign Dataset, and present an evaluation of tracking in the context of sign detection. We show that tracking essentially suppresses all false positives in our test set, and argue that in order to be useful for higher level analysis, any traffic sign detection system should contain tracking.

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“…In Equation (2) and (3) and    are defined as Equation (4), (5), and (6). The values for   and   are set to 0.1 and 0.05 respectively, in the experiment.…”

Section: Selection Of Transmitter Area Candidatesmentioning

confidence: 99%

Edge-Based Tracking of an LED Traffic Light for a Road-to-Vehicle Visible Light Communication System

Premachandra

Yendo²,

Tehrani³

et al. 2009

Journal of Broadcast Engineering

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We propose a visible light road-to-vehicle communication system at intersection as one of ITS technique. In this system, the communication between vehicle and a LED traffic light is approached using LED traffic light as a transmitter, and on-vehicle high-speed camera as a receiver. The LEDs in the transmitter are emitted in 500Hz and those emitting LEDs are captured by a high-speed camera for making communication. Here, the luminance value of each LED in the transmitter should be found for consecutive frames to achieve effective communication. For this purpose, first the transmitter should be identified, then it should be tracked for consecutive frames while the vehicle is moving, by processing the images from the high-speed camera. In our previous work, the transmitter was identified by getting the subtraction of two consecutive frames. In this paper, we mainly introduce an algorithm to track the identified transmitter in consecutive frames. Experimental results using appropriate images showed the effectiveness of the proposal.

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Real-time recognition of U.S. speed signs

Cited by 80 publications

References 20 publications

Detection of incomplete enclosures of rectangular shape in remotely sensed images

Detection of incomplete enclosures of rectangular shape in remotely sensed images

Traffic sign detection for U.S. roads: Remaining challenges and a case for tracking

Edge-Based Tracking of an LED Traffic Light for a Road-to-Vehicle Visible Light Communication System

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