&lt;title&gt;Fast vision-based vehicle detection algorithm using recognition of light pattern&lt;/title&gt;

Kim, Sung-Chang; Choi, Tae‐Sun

doi:10.1117/12.411587

Cited by 4 publications

(3 citation statements)

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“…Utilizing spatial information results in significant reduction of false positives compared to earlier approaches [1,2]. Investigating movement vector of the light-candidates prevents incidental noise lights aligned as car-lights being considered as a positive detection.…”

Section: Discussionmentioning

confidence: 99%

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Real-time video analysis for vehicle lights detection using temporal information

Eichner

Breckon

2007

IET 4th European Conference on Visual Media Production (CVMP 2007)

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Section: Discussionmentioning

confidence: 99%

“…Next, properties of the box bounding pair of car-light candidates (head-light candidates) are examined as proposed in [1]. In [2] Kim et. al.…”

Section: Previous Studiesmentioning

confidence: 99%

Real-time video analysis for vehicle lights detection using temporal information

Eichner

Breckon

2007

IET 4th European Conference on Visual Media Production (CVMP 2007)

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“…On the other hand, vision-based systems avoid interference problems. Furthermore, they are efficient 1 and are able to detect additional traffic features including lane markings and road signs 3 . Vision based systems have achieved the sophistication to demonstrate autonomous drivings 3 as well as the execution of collision avoidance manoeuvres 4 .…”

Section: Introductionmentioning

confidence: 99%

Night driving assistance system based on spatial perspective approach

Poh

2004

Machine Vision and Its Optomechatronic Applications

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In this paper we put forward and evaluate a near real-time night driving assistance system intended for use in land vehicles (cars in particular) to help with T-junctions crossing at night. The onboard system of the host vehicle computes the remaining distance between itself and the nearest approaching vehicle using spatial perspective method. The algorithm evaluates the interspacing of the incoming vehicle's headlights. This allows the distance-to-contact to be determined or estimated. This work emphasises techniques to obtain the required image quality for distance sensing. The image quality was achieved when work was focused primarily at the hardware levels. With polaroids in place, the acquired images show that the headlight signals are clearly distinguishable from other ambient lights. This significantly simplifies image processing. Road-testing shows rather promising results. The system can be generalised to intersection settings, prevent rear-front collisions and may be extended for daytime applications with the introduction of virtual references.

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An image based overexposed taillight detection method for frontal vehicle detection in night vision

Chien

Hang

Tseng

et al. 2016

2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)

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<title>Fast vision-based vehicle detection algorithm using recognition of light pattern</title>

Cited by 4 publications

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Real-time video analysis for vehicle lights detection using temporal information

Real-time video analysis for vehicle lights detection using temporal information

Night driving assistance system based on spatial perspective approach

An image based overexposed taillight detection method for frontal vehicle detection in night vision

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