Topic
Generalised Hough transform
About: Generalised Hough transform is a research topic. Over the lifetime, 56 publications have been published within this topic receiving 11460 citations. The topic is also known as: GHT.
Papers published on a yearly basis
Papers
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TL;DR: It is pointed out that the use of angle-radius rather than slope-intercept parameters simplifies the computation further, and how the method can be used for more general curve fitting.
Abstract: Hough has proposed an interesting and computationally efficient procedure for detecting lines in pictures. This paper points out that the use of angle-radius rather than slope-intercept parameters simplifies the computation further. It also shows how the method can be used for more general curve fitting, and gives alternative interpretations that explain the source of its efficiency.
6,693 citations
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TL;DR: It is shown how the boundaries of an arbitrary non-analytic shape can be used to construct a mapping between image space and Hough transform space, which makes the generalized Houghtransform a kind of universal transform which can beused to find arbitrarily complex shapes.
4,310 citations
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TL;DR: A form of the generalised Hough transform is used in conjuction with explicit probability-based voting models to find consistent matches and to identify the approximate poses of vehicles in traffic scenes, which under normal conditions stand on the ground-plane.
Abstract: Objects are often constrained to lie on a known plane. This paper concerns the pose determination and recognition of vehicles in traffic scenes, which under normal conditions stand on the ground-plane. The ground-plane constraint reduces the problem of localisation and recognition from 6 dof to 3 dof.
The ground-plane constraint significantly reduces the pose redundancy of 2D image and 3D model line matches. A form of the generalised Hough transform is used in conjuction with explicit probability-based voting models to find consistent matches and to identify the approximate poses. The algorithms are applied to images of several outdoor traffic scenes and successful results are obtained. The work reported in this paper illustrates the efficiency and robustness of context-based vision in a practical application of computer vision.
Multiple cameras may be used to overcome the limitations of a single camera. Data fusion in the proposed algorithms is shown to be simple and straightforward.
163 citations
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01 Dec 2013
TL;DR: A novel algorithm for fast tracking of generic objects in videos that makes use of the generalised Hough transform with pixel-based descriptors and a probabilistic segmentation method based on global models for foreground and background is presented.
Abstract: In this paper, we present a novel algorithm for fast tracking of generic objects in videos. The algorithm uses two components: a detector that makes use of the generalised Hough transform with pixel-based descriptors, and a probabilistic segmentation method based on global models for foreground and background. These components are used for tracking in a combined way, and they adapt each other in a co-training manner. Through effective model adaptation and segmentation, the algorithm is able to track objects that undergo rigid and non-rigid deformations and considerable shape and appearance variations. The proposed tracking method has been thoroughly evaluated on challenging standard videos, and outperforms state-of-the-art tracking methods designed for the same task. Finally, the proposed models allow for an extremely efficient implementation, and thus tracking is very fast.
141 citations
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TL;DR: Here it is shown that a single plane in parameter space can be employed, with a consequent gain in efficiency, and is especially suitable for ellipses of low eccentricity.
80 citations