Reliable detection and tracking of eyes is an important requirement for attentive user interfaces. In this paper we present a methodology for detecting eyes robustly in indoor environments in real-time. We exploit the...
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ISBN:
(纸本)0769506623
Reliable detection and tracking of eyes is an important requirement for attentive user interfaces. In this paper we present a methodology for detecting eyes robustly in indoor environments in real-time. We exploit the physiological properties and appearance of eyes as well as head/eye motion dynamics. Infrared lighting is used to capture the physiological properties of eyes, Kalman trackers are used to model eye/head dynamics, and a probabilistic based appearance model is used to represent eye appearance. By combining three separate modalities, with specific enhancements within each modality, our approach allows eyes to be treated as robust features that can be used for other higher-level processing.
When images captured by a tilted camera are mosaiced into a panorama, the resulting mosaic is curled. This happens, for example, with a panning camera that is not perfectly horizontal, and with a translating camera fa...
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When images captured by a tilted camera are mosaiced into a panorama, the resulting mosaic is curled. This happens, for example, with a panning camera that is not perfectly horizontal, and with a translating camera facing a tilled planar surface. The tilt of the camera causes differences in image velocity between the top and bottom parts of the image, causing the curled mosaic. In rectified mosaicing these distortions are overcome by warping the strips into rectangles, while keeping some image feature invariant. This warping equalizes the image motion at the different image parts, and the resulting mosaic is straight. Mosaicing is done without camera calibration or knowledge of the scene, and the process adapts automatically to smooth changes in the scene and the imaging conditions.
We present in this article a system, which improves a DEM The method reconstructs all the facades of the building and then, corrects the initial DEM by deleting the points of the roofs which pass or er the boundaries ...
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ISBN:
(纸本)0769506623
We present in this article a system, which improves a DEM The method reconstructs all the facades of the building and then, corrects the initial DEM by deleting the points of the roofs which pass or er the boundaries defined by the facades. We correct the shapes of the buildings with the initial photographs to hare sharp contours. The proposed approach does not use any a priori information about the orientation of the facades and the shape of the buildings. We present results with synthetic and real images.
Towards the goal of realizing a generic automatic human activity recognition system, a new formalism is proposed. Activities are described by a chained hierarchical representation using three type of entities: image f...
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ISBN:
(纸本)0769506623
Towards the goal of realizing a generic automatic human activity recognition system, a new formalism is proposed. Activities are described by a chained hierarchical representation using three type of entities: image features, mobile object properties and scenarios. Taking image features of tracked moving regions from an image sequence as input, mobile object properties are first computed by specific methods ods while noise is suppressed by statistical methods. Scenarios are recognized from mobile object properties based on Bayesian analysis. A sequential occurance several scenarios are recognized by an algorithm using a probabilistic finite-state automation (a variant of structured HMM). The demonstration of the optimality of these recognition method is discussed. Finally, the validity and the effectiveness of our approach is demonstrated on both real-world and perturbed data.
A specialized formulation of Azarbayejani and Pentland's framework for recursive recovery of motion, structure and focal length from feature correspondences tracked through an image sequence is presented. The spec...
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A specialized formulation of Azarbayejani and Pentland's framework for recursive recovery of motion, structure and focal length from feature correspondences tracked through an image sequence is presented. The specialized formulation addresses the case where all tracked points lie on plane. This planarity constraint reduces the dimension of the original state vector, and consequently the number of feature points needed to estimate the state. Experiments with synthetic data and real imagery illustrate the system performance. The experiments confirm that the specialized formulation provides improved accuracy, stability to observation noise, and rare of convergence in estimation for the case where the tracked points lie on a plane.
Histograms are used to analyze and classify images. They have been found experimentally to have low sensitivity to certain types of image morphisms, for example, viewpoint changes and object deformations. However;the ...
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ISBN:
(纸本)0769506623
Histograms are used to analyze and classify images. They have been found experimentally to have low sensitivity to certain types of image morphisms, for example, viewpoint changes and object deformations. However;the precise effect of these image morphisms on the histogram has not been studied. Irt this work we derive the complete class of local transformations that preserve the histogram or simply scale its magnitude. To achieve this the transformations are represented as solutions to families of vector fields acting on the image. It is then shown that weak perspective projection and paraperspective projection belong to this class and simply scale the histogram. The results on weak perspective projection, together with the effect of illumination, are used to compute the histogram of the projection of 3D polyhedral objects, We verify the analytical results with several examples. Moreover we present and test a system that recognizes and approximates the poses of 3D polyhedral objects independent of viewpoint.
This paper shows that the structure of the isobrightness contours in 'smooth' regions of a segmented image may be used to quantify the variation ill shading. Topographic terms are then appropriate for labellin...
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ISBN:
(纸本)0769506623
This paper shows that the structure of the isobrightness contours in 'smooth' regions of a segmented image may be used to quantify the variation ill shading. Topographic terms are then appropriate for labelling the X-inds of generic structure! that arise in smooth regions, domes, bowls, ridges, valleys, slopes and folds are quantifiable. The method uses contour context rather than filfer banks or a solution to the shape from shading problem to quantify the form of a region's brightness function. Region segmentation (distinguishing smooth from textured regions) is also performed with a largely filter free segmentation scheme with an brief outline of the scheme being given.
We propose blind segmentation of images into shape-related 'patches' based on pre-calculated local symmetries (Van Tender, G.J. & Ejima, Y. (1999). (Forthcoming a) Flexible computation of shape symmetries....
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We propose blind segmentation of images into shape-related 'patches' based on pre-calculated local symmetries (Van Tender, G.J. & Ejima, Y. (1999). (Forthcoming a) Flexible computation of shape symmetries. Submitted for publication) in shape boundary contours. First, lateral weights between all points in the boundary contour map are assigned analogous to Euclidean distance maps in watershed segmentation (Beucher, S. & Lantejoul, C. (1979). Use of watersheds in contour detection. proceedings of the International Workshop on imageprocessing. CCETT, Rennes, France.). Lateral weights are then used to: (1) extract local maxima in symmetries;(2) link maxima within locally enclosed boundary contours;and (3) reconstruct shape contours using symmetry maxima as 'seeds'. The new model overcomes weaknesses of watershed segmentation. The new model closes gaps in relatively more solid image contours, but it is fundamentally different from methods based on contour interpolation (Grossberg, S., Mingolla, E. & Todorove, D. (1989). A neural network architecture for preattentive vision, ieee Transactions on Biomedical Engineering 36, 65-84;Heitger, F. & von der Heydt, R. (1993). A computational model of neural contour processing. figure-ground segregation and illusory contours. proceedings of the Fourth International conference on computer Vision, ieeecomputersociety Press, Washington D.C. (pp. 32-40)). images are segmented into shape-relevant color-by-number-like patches which compare well to related methods (Gauch, J. & Pizer, M. (1993). The intensity axis of symmetry and its application to image segmentation, ieee Transactions on pattern Analysis and Machine Intelligence, 15 (8), 753-770;Ilg, W. & Ogniewicz, R. (1995). The application of Voronoi skeletons to perceptual grouping in line images, proceedings of the 11th International conference on patternrecognition, The Hague, The Netherlands, pp. 382-385;Zhu, S.C. & Yuille, A.L. (1996) FORMS: a flexible object recognition and mo
The detection and recognition of events is a challenging problem in video databases. It involves crosslinking and combining information available in, multiple modalities such as audio, video and associated text metada...
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The detection and recognition of events is a challenging problem in video databases. It involves crosslinking and combining information available in, multiple modalities such as audio, video and associated text metadata. CueVideo is a system designed far the discovery and recognition of specific events called topics of discussion through advanced video summarization and cross-modal indexing. It supports search for relevant video content through several modes of video summarization including storyboards, moving storyboards and time-scale modified audio summarization. It also enables the recognition and indexing of topical events through cross-modal search of audio and video content based on text and image queries respectively.
We introduce a fast, multiscale algorithm for image segmentation. Our algorithm uses modern numeric techniques to find an approximate solution to normalized cut measures in time that is linear in the size of the image...
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ISBN:
(纸本)0769506623
We introduce a fast, multiscale algorithm for image segmentation. Our algorithm uses modern numeric techniques to find an approximate solution to normalized cut measures in time that is linear in the size of the image with only a few dozen operations per pixel. In just one pass the algorithm provides a complete hierarchical decomposition of the image into segments. The algorithm detects the segments by applying a process of recursive coarsening in which the same minimization problem is represented with fewer and fewer variables producing an irregular pyramid. During this coarsening process we may compute additional internal statistics of the emerging segments and use these statistics to facilitate the segmentation process. Once the pyramid is completed it is scanned from the top down to associate pixels close to the boundaries of segments with the appropriate segment. The algorithm is inspired by algebraic multigrid (AMG) solvers of minimization problems of heat or electric networks. We demonstrate the algorithm by applying it to real images.
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