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Book ChapterDOI

Intensity and Edge-Based Symmetry Detection Applied to Car-Following

TLDR
Two methods for detecting symmetry in images are presented, one based directly on the intensity values and another one based on a discrete representation of local orientation, which is applied to the problem of visually guided car-following.
Abstract
We present two methods for detecting symmetry in images, one based directly on the intensity values and another one based on a discrete representation of local orientation. A symmetry finder has been developed which uses the intensity-based method to search an image for compact regions which display some degree of mirror symmetry due to intensity similarities across a straight axis. In a different approach, we look at symmetry as a bilateral relationship between local orientations. A symmetryenhancing edge detector is presented which indicates edges dependent on the orientations at two different image positions. SEED, as we call it, is a detector element implemented by a feedforward network that holds the symmetry conditions. We use SEED to find the contours of symmetric objects of which we know the axis of symmetry from the intensity-based symmetry finder. The methods presented have been applied to the problem of visually guided car-following. Real-time experiments with a system for automatic headway control on motorways have been successful.

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Book

Computational Symmetry in Computer Vision and Computer Graphics

TL;DR: Recognizing the fundamental relevance and group theory of symmetry has the potential to play an important role in computational sciences.
Patent

Collision warning system

TL;DR: In this paper, a method of estimating a time to collision (TTC) of a vehicle with an object comprising: acquiring a plurality of images of the object; and determining a TTC from the images that is responsive to a relative velocity and relative acceleration between the vehicle and the object.
Patent

Method and apparatus for machine vision classification and tracking

TL;DR: In this article, a machine vision system acquires images with a video camera from roadway scenes and processes the images by analyzing the intensities of edge elements within the image, then applies fuzzy set theory to the location and angles of each pixel after the pixel intensities have been characterized by vectors.
Journal ArticleDOI

Systems for Safety and Autonomous Behavior in Cars: The DARPA Grand Challenge Experience

TL;DR: In this paper, the authors present a multisensor platform that combines different sensing modalities that inherently yield uncertain information for fully autonomous off-road driving in the Grand Challenge 2017 and 2018.

Systems for Safety and Autonomous Behavior in Cars: The DARPA Grand Challenge Experience Car safety systems are helping drivers to stay in their lanes, improving their night vision and are making driving decisions where millisecond response is needed.

TL;DR: The intent of the paper is to evaluate approaches and technologies used in the two Grand Challenges as they contribute to the needs of autonomous cars on the road.
References
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Journal ArticleDOI

Finding axes of skewed symmetry

TL;DR: A heuristic symmetry evaluator is used in conjunction with a constraint to determine axes of skewed symmetry in a planar skew symmetric figure which constrains, them to lie on a one-dimensional locus in a two-dimensional space of orientation pairs.
Journal ArticleDOI

Using symmetry for detecting and locating objects in a picture

TL;DR: The template matching procedure works directly in conjunction with unscaled intensity images, independently of position and orientation, and may be adapted to the case of overlapping objects by introducing the concept of local symmetry.
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