A compendium of NP optimization problems, containing the best approximation results known for each problem, is now available on the web at http://***/~viggo/problemlist/. In this paper we describe such a compendium, a...
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Embodiment and subjectivity are important research issues for collaborative virtual environments. The authors claim that the direction and distance of an embodiment are the most important indicators of the relation be...
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Embodiment and subjectivity are important research issues for collaborative virtual environments. The authors claim that the direction and distance of an embodiment are the most important indicators of the relation between a user and surrounding objects or other users. In an objective view of a virtual environment embodiment motion is unambiguous since all users will see all other users and all artifacts in the same positions. However there are many reasons to present different views of the same basic data set to different users. If objects end up in different positions in different views, one cannot retain a common coordinate system for the embodiments, since directions and distances are distorted. They present an implementation of artifact-centred coordinate mappings by which the positions of the artifacts that the user is interacting with govern how that user is represented to other users of the system.
The characteristics of a project course (160 h of work for the students) oriented towards graphical interaction is described. Project proposals are presented to the students by researchers from different applications....
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The characteristics of a project course (160 h of work for the students) oriented towards graphical interaction is described. Project proposals are presented to the students by researchers from different applications. The students get a high degree of freedom during the project and partly as a result of this they are enthusiastic about the work and produce very impressive prototypes which they present at the end of the course. Copyright (C) 1996 Elsevier science Ltd
We present an integrated system which is able to pursue a moving object and maintain the object centered in the image by controlling a robot-head. The system contains three parts: independent motion detection, trackin...
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We present an integrated system which is able to pursue a moving object and maintain the object centered in the image by controlling a robot-head. The system contains three parts: independent motion detection, tracking, and control of a robot-head. This paper focuses on the detection mechanism, and briefly discusses the tracking and control issues. The system runs continuously in time and updates the object localization at a frame-rate of 25 Hz. The moving object can be tracked, although the observer performs an unknown independent motion, involving both translation and rotation. We focus on a simple motion detection algorithm, since computational cost is of major importance for real-time systems with feedback. The algorithm is noniterative and computationally inexpensive. The running time complexity is O(n) for an image containing n pixels. The image-processing takes place on a MaxVideo200 pipeline processor, and the head control algorithm is running on a Transputer T800 network. Some offline experimental results are presented, where comparisons are made between affine and translational image motion models.
Fixation is the link between the physical environment and the visual observer, both of which can be dynamic. That is, dynamic fixation serves the task of preserving a reference point in the world, despite relative mot...
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Fixation is the link between the physical environment and the visual observer, both of which can be dynamic. That is, dynamic fixation serves the task of preserving a reference point in the world, despite relative motion. In this respect, fixation is dynamical in two senses: in response to voluntary changes of fixation point or attentive cues-gaze shiftings, and in response to the desire to compensate for the retinal slip-gaze holding. The work presented here, addresses the vergence movement and preservation of binocular fixation during smooth pursuit. This movement is a crucial component of fixation. The two vergence processes, disparity vergence and accommodative vergence, are described;a novel algorithm for robust disparity vergence and an active approach for blur detection and depth from defocus are presented. The main characteristics of the disparity vergence technique are the simplicity of the algorithm, the influence of both left and right images in the course of fixation and the agreement with the fixation model of primates. The major characteristic of the suggested algorithm for blur detection is its active approach which makes it suitable for achieving qualitative and reasonable depth estimations without unrealistic assumptions about the structures in the images. The paper also covers the integration of the two processes disparity vergence and accommodation vergence which are in turn accomplished by an integration of the disparity and blur stimuli. This integration is accounted for in both static and dynamic experiments.
It is well-known that active selection of fixation points in humans is highly context and task dependent. It is therefore likely that successful computational processes for fixation in active vision should be so too. ...
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It is well-known that active selection of fixation points in humans is highly context and task dependent. It is therefore likely that successful computational processes for fixation in active vision should be so too. We are considering active fixation in the context of recognition of man-made objects characterized by their shapes. In this situation the qualitative shape and type of observed junctions play an important role. The fixations are driven by a grouping strategy, which forms sets of connected junctions separated from the surrounding at depth discontinuities. We have furthermore developed a methodology for rapid active detection and classification of junctions by selection of fixation points. The approach is based on direct computations from image data and allows integration of stereo and accommodation cues with luminance information. This work form a part of an effort to perform active recognition of generic objects, in the spirit of Malik and Biederman, but on real imagery rather than on line-drawings.
This paper deals with the problems on the recovery and shape and motion. It also focuses on what is representing shape. In addition, it touches a briefly on the geometry for computer vision which concerns surface mode...
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This paper deals with the problems on the recovery and shape and motion. It also focuses on what is representing shape. In addition, it touches a briefly on the geometry for computer vision which concerns surface modeling. However, this paper goes beyond the need to model geometry and shape for computer vision, in that is also aims at developing mathematically well-founded computational environments for studying geometry by itself.
An algorithm is presented for computing a decomposition of planar shapes into convex subparts represented by ellipses, The method is invariant to projective transformations of the shape, and thus the conic primitives ...
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An algorithm is presented for computing a decomposition of planar shapes into convex subparts represented by ellipses, The method is invariant to projective transformations of the shape, and thus the conic primitives can be used for matching and definition of invariants in the same way as points and lines. The method works for arbitrary planar shapes admitting at least four distinct tangents and it is based on finding ellipses with four points of contact to the given shape. The cross ratio computed from the four points on the ellipse can then be used as a projectively invariant index. It is demonstrated that a given shape has a unique parameter-free decomposition into a finite set of ellipses with unit cross ratio. For a given shape, each pair of ellipses can be used to compute two independent projective invariants. The set of invariants computed for each ellipse pair can be used as indexes to a hash table from which model hypothesis can be generated Examples of shape decomposition and recognition are given for synthetic shapes and shapes extracted from grey level images of real objects using edge detection.
This paper addresses the problem of computing cues to the three-dimensional structure of surfaces in the world directly from the local structure of the brightness pattern of either a single monocular image or a binocu...
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This paper addresses the problem of computing cues to the three-dimensional structure of surfaces in the world directly from the local structure of the brightness pattern of either a single monocular image or a binocular image pair. It is shown that starting from Gaussian derivatives of order up to two at a range of scales in scale-space, local estimates of (i) surface orientation from monocular texture foreshortening, (ii) surface orientation from monocular texture gradients, and (iii) surface orientation from the binocular disparity gradient can be computed without iteration or search, and by using essentially the same basic mechanism. The methodology is based on a multi-scale descriptor of image structure called the windowed second moment matrix, which is computed with adaptive selection of both scale levels and spatial positions. Notably, this descriptor comprises two scale parameters;a local scale parameter describing the amount of smoothing used in derivative computations, and an integration scale parameter determining over how large a region in space the statistics of regional descriptors is accumulated. Experimental results for both synthetic and natural images are presented, and the relation with models of biological vision is briefly discussed.
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