Publication

Ball Detection and Predictive Ball Following Based on a Stereoscopic Vision System

Davide Scaramuzza
2005
Conference Papers

Abstract

In this paper we describe an efficient software architecture for object-tracking, based on a stereoscopic vision system, that has been applied to a mobile robot controlled by a PC. After analyzing the epipolar rectification required to correct the original stereo-images, it is described a new valid and efficient algorithm for ball recognition (indeed circle detection) which is able to work in different lighting conditions and in a manner faster than some modified versions of Circle Hough Transform. Then, we show that stereo vision, besides giving an optimum estimation of the 3D position of the object, is useful to remove lots of the false identifications of the ball, thanks to the advantages of epipolar constraint. Finally, we describe a new strategy for ball following, by a mobile robot, which is able to look for the object whenever it comes out of the cameras view, by taking advantage of a block matching method similar to that of MPEG Video.

Official source

https://infoscience.epfl.ch/entities/publication/cb95e9a3-6bc6-4fe2-a6c8-6608ae1bbaf9

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Davide Scaramuzza
2005
Conference Papers

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/cb95e9a3-6bc6-4fe2-a6c8-6608ae1bbaf9

About this result

Ontological neighbourhood

Information engineering

Artificial intelligence: Computer vision

Related concepts (32)

Computer stereo vision

Computer stereo vision is the extraction of 3D information from digital images, such as those obtained by a CCD camera. By comparing information about a scene from two vantage points, 3D information can be extracted by examining the relative positions of objects in the two panels. This is similar to the biological process of stereopsis. In traditional stereo vision, two cameras, displaced horizontally from one another, are used to obtain two differing views on a scene, in a manner similar to human binocular vision.

Image rectification

Image rectification is a transformation process used to project images onto a common image plane. This process has several degrees of freedom and there are many strategies for transforming images to the common plane. Image rectification is used in computer stereo vision to simplify the problem of finding matching points between images (i.e. the correspondence problem), and in geographic information systems to merge images taken from multiple perspectives into a common map coordinate system.

Stereopsis

Stereopsis () is the component of depth perception retrieved through binocular vision. Stereopsis is not the only contributor to depth perception, but it is a major one. Binocular vision happens because each eye receives a different image because they are in slightly different positions on one's head (left and right eyes). These positional differences are referred to as "horizontal disparities" or, more generally, "binocular disparities". Disparities are processed in the visual cortex of the brain to yield depth perception.

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