Author name cluster

Daniel DeMenthon

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

5 papers

1 author row

ICRA Conference 1992 Conference Paper

Navigation with uncertainty: reaching a goal in a high collision risk region

Philippe Burlina
Daniel DeMenthon
Larry S. Davis

The authors describe a computational framework in which a probabilistic method for noisy sensor-based robotic navigation in dynamic environments can be devised. The aim of the method is to generate an optimal trajectory by considering as optimality criteria the probability of not colliding with the obstacles and the probability of accessing an operational position with respect to a moving target object. A formal framework in which the probability of collision associated with an elementary robot displacement can be calculated is discussed. Estimates on the obstacle kinematic parameters and measures of confidence on these estimates are used to produce the probability of collision associated with any robot displacement. The probability of collision is derived in two steps: a stochastic model is defined in the kinematic state space of the obstacles and collision events are given a simple geometric characterization in this state space. >

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ICRA Conference 1990 Conference Paper

Fast range scanner using an optic RAM

Tsutomu Ito
Daniel DeMenthon
Larry S. Davis

A range scanner which calculates ranges by triangulation between the incident angles of laser stripes and the positions of their images on a camera sensor was developed for robotic applications. It uses a solid-state image sensor called Optic RAM instead of a CCD sensor. This sensor chip has three desirable characteristics for the position detection of laser stripes in images: it thresholds the image, detecting only the brighter stripes in binary form; it is an image memory; and pixel values can be addressed randomly in the image. Thus, the design does not require an A/D converter or a frame buffer and is consequently inexpensive. For improved performance, only the image region next to the previous stripe location is searched, and a 64-KB lookup table stored in RAM is indexed by incident laser angles and stripe addresses to output range data. A 128*256 range image is produced in about 20 s. This is reasonably fast considering that this process requires analyzing 256 images. The speed bottleneck is the low sensitivity of the optic RAM chip, which requires a long exposure time per frame (60 ms), corresponding to half the standard video frame rate. Simple calibration methods using planar patterns of parallel lines are presented. >

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ICRA Conference 1990 Conference Paper

New exact and approximate solutions of the three-point perspective problem

Daniel DeMenthon
Larry S. Davis

An exact method for computing the position of a triangle in space from its image is presented. Also presented is an approximate method based on orthoperspective, an approximation of perspective which produces lower errors for off-center triangle images than scaled orthographic projection. A comparison is made of exact and approximate solutions for the triangle pose. This comparison gives the relative combinations of image and triangle characteristics which are likely to generate the largest errors. Model-based pose estimation techniques which match image and model triangles require large numbers of matching operations in real-world applications. It is shown that the approximate model can be used to build lookup tables for each of the triangles of a model and that they speed up the estimation of an object pose. >

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ICRA Conference 1990 Conference Paper

Reconstruction of a road by local image matches and global 3D optimization

Daniel DeMenthon
Larry S. Davis

A method is presented for reconstructing a 3-D road from a single image. It finds the images of opposite points of the road. Opposite points are points which face each other on the opposite sides of the road; the images of these points are called matching points. For points chosen from one side of the road image, the algorithm finds all the matching point candidates on the other side, based on local properties of a road. However, these solutions do not necessarily satisfy the global properties of a typical road. A dynamic programming algorithm is applied to reject the candidates which do not fit the global road. A benchmark using synthetic roads is described. It shows that the roads reconstructed by the proposed method match the actual roads better than those reconstructed by two other road reconstruction algorithms. Experiments with 50 road images taken by the autonomous land vehicle (ALV) showed that the method is robust with real-world data and that the reconstructions are fairly consistent with road profiles obtained by fusion between range images and video images. >

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ICRA Conference 1987 Conference Paper

A zero-bank algorithm for inverse perspective of a road from a single image

Daniel DeMenthon

A method is presented for reconstructing the 3-D geometry of a road from a single image of the road. This problem has an infinity of solutions unless restrictive hypotheses about geometric characteristics of this road are assumed. The road is modeled as a space ribbon defined by a spine (centerline) and generators (cross-segments) which are horizontal line segments cutting the spine at their midpoint at a normal angle. Properties of two neighboring generators of such a ribbon are examined; if a generator is known, a neighboring generator is completely defined if one of its ends is known. The proposed method uses this property to reconstruct the visible part of the world road, by iteratively finding a series of generators. This method is tested against a simple method which assumes that the ground is flat ("Flat Earth assumption"), and against another method which uses vanishing points.

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