The velocity Hough transform: a new technique for dynamic feature extraction

Nash, Jason M.; Carter, J.N.; Nixon, Mark S.

doi:10.1109/icip.1997.638786

Cited by 10 publications

(3 citation statements)

References 5 publications

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“…Application of Hough Transform to temporal observation spaces can potentially have a large impact in many domains other than image analytics. While Hough Transform has been a popular technique for detecting shapes from images [16], its applications to temporal observation spaces, in addition to 2D/3D imagery spaces, have been also studied for motion detections [18,13]. In general, the approach could be applicable to any problem of detecting patterns from spatio-temporal observations.…”

Section: Related Workmentioning

confidence: 99%

A Probabilistic Hough Transform for Opportunistic Crowd-sensing of Moving Traffic Obstacles

Tatsubori

Walcott-Bryant

Bryant

et al. 2018

Proceedings of the 2018 SIAM International Conference on Data Mining

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Traffic congestion in developing cities like Nairobi, Kenya can be significantly impacted by the presence of Moving Traffic Obstacles (MTOs). These MTOs are events that temporarily exist on the road, moving with or against the direction of traffic at slower speeds. They include two-wheelers, pushcarts, animals, and pedestrians, which have quite different influence on traffic compared with static obstacles, such as potholes and speed bumps. As smartphones and supporting 3G infrastructures are wide spread even in developing countries, recent studies enabled frugal traffic obstacle data collection from smartphones in probe cars. Assuming the opportunistic, unevenly-distributed, sparse and errorful observation of traffic obstacles, we propose an MTO detection algorithm extending an image analysis technique called Probabilistic Hough Transform for collective observations as input. Based on our experiences with a small set of real-world data collected in a smartphonebased probe car project with Nairobi City County, we conducted experiments with simulated observation data to see the effectiveness of the algorithm.

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Section: Related Workmentioning

confidence: 99%

A Probabilistic Hough Transform for Opportunistic Crowd-sensing of Moving Traffic Obstacles

Tatsubori

Walcott-Bryant

Bryant

et al. 2018

Proceedings of the 2018 SIAM International Conference on Data Mining

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“…Hough transform is an image feature extraction technique that identifies lines in an image. The detected lines are then used in the determination of the amount of vibration and then proper image registration (transformation to match base image) is carried out [1]. Also, the luminosity of the acquired images is used to calculate the amount of glare detected in an image and then intensity histogram is balanced to enhance the output image.…”

Section: Introductionmentioning

confidence: 99%

Application of hough transform feature extraction to reduce angular vibration in images captured from moving objects

Afolabi

Man

Liang

et al. 2013

2013 International SoC Design Conference (ISOCC)

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This paper details an ongoing research aimed at developing computational approach to reducing/eliminating vibration and light glare in images captured by digital cameras especially when the scene contains moving objects or the camera is mounted on a moving vehicle / flying drone. The algorithms developed are focused at real-time image acquisition where the enhanced/corrected images are need almost immediately after they are captured. The results show that these methods of reducing the stated problems are effective and it can be further developed for various applications.

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“…While this approach does perform velocity estimation, it is unclear how it might handle congested traffic scenes. In yet another approach, researchers advocated use of the velocity Hough transform to simultaneously extract the velocity and position of vehicles (8). However, this method probably cannot handle images containing many objects.…”

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confidence: 99%

Correlation Technique for Estimating Traffic Speed from Cameras

Schoepflin

Dailey

2003

Transportation Research Record: Journal of the Transportation R

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A new algorithm is presented for estimating speed from roadside cameras in uncongested traffic, congested traffic, favorable weather conditions, and adverse weather conditions. Individual vehicle lanes are identified and horizontal vehicle features are emphasized by using a gradient operator. The features are projected into a one-dimensional subspace and transformed into a linear coordinate system by using a simple camera model. A correlation technique is used to summarize the movement of features through a group of images and estimate mean speed for each lane of vehicles.

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The velocity Hough transform: a new technique for dynamic feature extraction

Cited by 10 publications

References 5 publications

A Probabilistic Hough Transform for Opportunistic Crowd-sensing of Moving Traffic Obstacles

A Probabilistic Hough Transform for Opportunistic Crowd-sensing of Moving Traffic Obstacles

Application of hough transform feature extraction to reduce angular vibration in images captured from moving objects

Correlation Technique for Estimating Traffic Speed from Cameras

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