Abstract: The matching process includes: finding first and second three-dimensional reconstruction point sets that contain three-dimensional position coordinates of segments, and first and second feature set that contain three-dimensional information regarding vertices of the segments, from image data of an object (S2 to S4); and matching the first feature set with the second feature set, thereby determining a corresponding point of the first and second three-dimensional reconstruction point sets (S5 to S10), wherein Step S5 carries out initial matching with respect to the segments; Step S6 selects a feature point from the first feature set; Step S7 specifies an adjustment region containing the selected feature point; Step S8 carries out fine adjustment of matching with respect to the segments within the adjustment region; and Steps S6 to S8 are performed at each increase of the adjustment region and at each selection of the feature point.

Abstract: The device includes: an input unit (4) for receiving image data obtained by capturing images of an object by imaging units (C1 to C3); and an arithmetic unit (1) that performs: 1) finding a three-dimensional reconstruction point set that contain three-dimensional position information of segments obtained by dividing a boundary of the object in the image data, and a feature set that contain three-dimensional information regarding vertices of the segments, for each of multiple pairs of two different images; 2) calculating a total three-dimensional reconstruction point set and a total feature set by totaling the three-dimensional reconstruction point sets and the feature sets of the multiple pairs; and 3) matching a model feature set regarding model data of the object with the total feature set, thereby determining, among the total three-dimensional reconstruction point set, points corresponding to model points of the object.

Abstract: An object movement tracking apparatus and its method tracks an object with an unknown initial position and which object is continually moving, the apparatus for recovering a tracking process even when the tracking has failed and includes an observing device such as a video camera for observing a scene at a video frame rate. Time-sequentially acquired image data from the observing device are stored in an image memory device and the data processed in parallel. During data processing, an object recognition module selects a frame memory based on predetermined information. An estimated value of position/posture of the object are calculated from the image data and transmitted. A movement tracking module receives transmitted data from the object recognition module, replacing a current frame with a next frame and waits until image data in the next frame are inputted.

Abstract: After stereo image is inputted (S1), the tracing point corresponding to the silhouette of a curved object observed by the stereo image is selected on the basis of the information on the present position of the object (S2), using a three-dimensional geometric model. And the corresponding points on the silhouette corresponding to respective tracing points are sampled from the stereo image (S3), and their three-dimensional coordinates are measured (S4). Then, from the group of the three-dimensional coordinates of tracing points and corresponding points, the position/posture of the object concerned and the measurement error are determined (S5), to discriminate the error (S6).

Abstract: The objective of the present invention is to provide an object movement tracking apparatus and its method capable of dealing with an object with an unknown initial position and a continually moving object and capable of recovering a tracking process even when the tracking is failed.

Abstract: An image processing method and an apparatus therefor calculating the rotations and the magnifications of a plurality of image pick-up devices, which are located at different positions and rotations and rotates, and pick-up images of the same object in a three-dimensional space, from the following equation by matching the image picked-up by the two arbitrary image pick-up devices, extracting the corresponding points, and detecting the coordinates values thereof on each image, ##EQU1## where, {expression}.sub.y : y component of the expression,{expression}.sub.z : z component of the expression,x,y,z: coordinate values of a point in a three-dimensional space,X.sub.L ', Y.sub.L ', X.sub.R ', Y.sub.R ': coordinate values of x, y on both images,.theta..sub.L, .phi..sub.L, .alpha..sub.L, .phi..sub.R, .alpha..sub.R,: differences in the rotation from the x-, y-, and z-axes of both image pick-up devices from the state to become a reference,f.sub.L,f.sub.R : magnifications of both image pick-up devices.

Abstract: A method of processing image information is disclosed, for recognizing the position and attitude of an object with a high speed treatment and improved recognition accuracy. The method comprised of the steps of entry of a stereoscopic image of an object, extraction of edges of the object, and dividing it into segments based on the local feature of the image, adding the apex information to the segments to produce the recognition data, verifying the recognition data with reference to an object model based on local geometric features to detect a corresponding candidate; finely adjusting each of corresponding candidates based on an entire geometric features; and detecting the position and attitude of the object on the basis of recognition including the initial verification and the fine adjustment.

Abstract: A method of processing image information is disclosed, for detecting the movement of an object with a simplifed system structure, and high speed treatment. The method is comprised of the steps of entry of a stereoscopic image of an object, extraction of edges of the object, and dividing it into segments based on the local feature of the image. On each segment, tracing points (sampling points) are selected, the inter-frame correlation of selected points is obtained, the three-dimensional coordinates of the points are measured, and thus the position and attitude of the object are detected, wherein the inter-frame correlation is performed by evaluating the similarity between frames based on correlation between the tangential direction of tracing points and the luminance value of the surface.

Abstract: An image processing method for matching edges detected in images of the same objects in a three-dimensional scene which are taken simultaneously by two or more image pick-up devices at different positions, in which the boundary segments on the edges are classified into apparently real segments, apparently imaginary segments or undefined segments, a planar surface is found for each boundary which has all apparently real segments and no apparently imaginary segment on it by using the information of the points of occlusion, the surface is regarded as the real surface in the case where there is only one surface which has no segment under it, so that surface information and the distance information at arbitrary points on the real surface are obtained.