LANA: a lane extraction algorithm that uses frequency domain features

Kreucher, Chris; Lakshmanan, Sridhar

doi:10.1109/70.760356

Cited by 141 publications

(61 citation statements)

References 22 publications

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“…Most extraneous image lines are rejected by the symmetric dark-light-dark assumption, metric width and length thresholds, and curvature constraints; straight and curved segments observed from any perspective are handled uniformly, unlike template-based (Taylor et al 1999;Pomerleau and Jochem 1996) or frequency-based (Kreucher and Lakshmanan 1999) techniques; and features are reliably extracted even under variations in road texture and scene illumination, unlike intensity analysis techniques (Arbib and Pomerleau 1995;Baluja 1996).…”

Section: Road Paint From Symmetric Contoursmentioning

confidence: 99%

Finding multiple lanes in urban road networks with vision and lidar

et al. 2009

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This paper describes a system for detecting and estimating the properties of multiple travel lanes in an urban road network from calibrated video imagery and laser range data acquired by a moving vehicle. The system operates in real-time in several stages on multiple processors, fusing detected road markings, obstacles, and curbs into a stable non-parametric estimate of nearby travel lanes. The system incorporates elements of a provided piecewise-linear road network as a weak prior.Our method is notable in several respects: it detects and estimates multiple travel lanes; it fuses asynchronous, heterogeneous sensor streams; it handles high-curvature roads; and it makes no assumption about the position or orientation of the vehicle with respect to the road.We analyze the system's performance in the context of the 2007 DARPA Urban Challenge. With five cameras and thirteen lidars, our method was incorporated into a closedloop controller to successfully guide an autonomous vehicle through a 90 km urban course at speeds up to 40 km/h amidst moving traffic.

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Section: Road Paint From Symmetric Contoursmentioning

confidence: 99%

Finding multiple lanes in urban road networks with vision and lidar

et al. 2009

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“…In urban areas and on highways, visual road detection is carried out by detection of lane markers. A common approach is to reproject the image onto the ground plane followed by line detection in the resampled image [1,6,7]. Using other sensors such as Lidar, similar lane detection approaches are used [5].…”

Section: Railway Vs Road Detectionmentioning

confidence: 99%

Detecting Rails and Obstacles Using a Train-Mounted Thermal Camera

et al. 2015

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Abstract. We propose a method for detecting obstacles on the railway in front of a moving train using a monocular thermal camera. The problem is motivated by the large number of collisions between trains and various obstacles, resulting in reduced safety and high costs. The proposed method includes a novel way of detecting the rails in the imagery, as well as a way to detect anomalies on the railway. While the problem at a first glance looks similar to road and lane detection, which in the past has been a popular research topic, a closer look reveals that the problem at hand is previously unaddressed. As a consequence, relevant datasets are missing as well, and thus our contribution is two-fold: We propose an approach to the novel problem of obstacle detection on railways and we describe the acquisition of a novel data set.

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“…Energy function E snake of snake v(s), s ∈ [0, 1], is defined as (6). The estimation of snake is to find snake v (s) which minimize E snake .…”

Section: Parallel Snakesmentioning

confidence: 99%

“…Lane boundaries were modeled to be straight in [2]- [4], while researchers in [5] described lanes as piecewise lines to achieve better accuracy. Moreover, parabolas were used in [6], [7] and B-snake was proposed in [8], [9] with the best flexibility. Most of them described each sides of lane boundaries separately, but only [10], [11] took the parallel property of two boundaries into consideration.…”

Section: Introductionmentioning

confidence: 99%

Parallel-Snake with Balloon Force for Lane Detection

Fang

2014

IEICE Trans. Inf. & Syst.

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SUMMARYLane detection plays an important role in Driver Assistance Systems and Autonomous Vehicle System. In this paper, we propose a parallel-snake model combined with balloon force for lane detection. Parallel-snake is defined as two open active contours with parallel constrain. The lane boundaries on the left and right sides are assumed as parallel curves, parallel-snake is deformed to estimate these two boundaries. As lane regions between left and right boundaries usually have low gradient, snake will lose external force on these regions. Furthermore, inspired by balloon active contour model, the balloon force is introduced into parallel-snake to expand two parallel curves from center of road to the left and right lane boundaries. Different from closed active contour, stretching force is adopted to prevent the head and tail of snake from converging together. The experimental results on three different datasets show that parallel-snake model can work well on images with shadows and handle the lane with broken boundaries as the parallel property.

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LANA: a lane extraction algorithm that uses frequency domain features

Cited by 141 publications

References 22 publications

Finding multiple lanes in urban road networks with vision and lidar

Finding multiple lanes in urban road networks with vision and lidar

Detecting Rails and Obstacles Using a Train-Mounted Thermal Camera

Parallel-Snake with Balloon Force for Lane Detection

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