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Journal ArticleDOI

Determining object motion in a sequence of stereo images

Yeon Taik Kim, +1 more
- Vol. 3, Iss: 6, pp 599-614
TLDR
A two-pass relaxation method is developed for matching features extracted from successive depth maps, based on the principle of conservation of distance and angle between features during rigid motion.
Abstract
The motion of a three-dimensional object is determined from a sequence of stereo images by extracting three-dimensional features, establishing correspondences between these features, and finally, computing the rigid motion parameters. Three-dimensional features are extracted from the depth map of a scene. A two-pass relaxation method is developed for matching features extracted from successive depth maps. In each iteration, geometrical relationships between a feature and its neighbors in one map are compared to those between a candidate in the other map and its neighbors to update the matching probability of the candidate. The comparison of the geometrical relationship is based on the principle of conservation of distance and angle between features during rigid motion. The use of three-dimensional features allows one to find the rotation and translation components of motion separately via solving linear equations. Experimental results using several sets of real data are presented to illustrate results and difficulties.

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Citations
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Journal ArticleDOI

Human and machine recognition of faces: a survey

TL;DR: A critical survey of existing literature on human and machine recognition of faces is presented, followed by a brief overview of the literature on face recognition in the psychophysics community and a detailed overview of move than 20 years of research done in the engineering community.
Journal ArticleDOI

On the computation of motion from sequences of images-A review

TL;DR: Two distinct paradigms are highlighted: (i) the feature- based approach and (ii) the optical-flow-based approach: the comparative merits/demerits of these approaches are discussed.
Journal ArticleDOI

Computation and analysis of image motion: a synopsis of current problems and methods

TL;DR: A structured synopsis of the problems in image motion computation and analysis, and of the methods proposed, exposing the underlying models and supporting assumptions are offered.
Journal ArticleDOI

Estimating the kinematics and structure of a rigid object from a sequence of monocular images

TL;DR: Results of an experiment with real imagery are presented, involving estimation of 28 unknown translational, rotational, and structural parameters, based on 12 images with seven feature points.
Journal ArticleDOI

Three-dimensional motion computation and object segmentation in a long sequence of stereo frames

TL;DR: The motion computation problem is formulated as a tracking problem in order to apply the extended Kalman filter and the tracking is performed in a prediction-matching-update loop in which multiple matches can be handled.
References
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Journal ArticleDOI

Use of the Hough transformation to detect lines and curves in pictures

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.
Journal ArticleDOI

A computer algorithm for reconstructing a scene from two projections

TL;DR: A simple algorithm for computing the three-dimensional structure of a scene from a correlated pair of perspective projections is described here, when the spatial relationship between the two projections is unknown.
Journal ArticleDOI

Uniqueness and Estimation of Three-Dimensional Motion Parameters of Rigid Objects with Curved Surfaces

TL;DR: In this article, it was shown that seven point correspondences are sufficient to uniquely determine from two perspective views the three-dimensional motion parameters (within a scale factor for the translations) of a rigid object with curved surfaces.
Journal ArticleDOI

On the Analysis of Accumulative Difference Pictures from Image Sequences of Real World Scenes

TL;DR: Analysis of a first-order difference picture (FODP) provides a separate estimate for images of moving objects and of stationary scene components that represents the stationary scene component in a TV-image sequence.
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