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.
We present a technique to reduce image blur caused by out-of-focus regions in projected imagery. Unlike traditional restoration algorithms that operate on a blurred image to recover the original, the nature of our pro...
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Plenoptic cameras are gaining attention for their unique light gathering and post-capture processing capabilities. We describe a decoding, calibration and rectification procedure for lenselet-based plenoptic cameras a...
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ISBN:
(纸本)9780769549897
Plenoptic cameras are gaining attention for their unique light gathering and post-capture processing capabilities. We describe a decoding, calibration and rectification procedure for lenselet-based plenoptic cameras appropriate for a range of computervision applications. We derive a novel physically based 4D intrinsic matrix relating each recorded pixel to its corresponding ray in 3D space. We further propose a radial distortion model and a practical objective function based on ray reprojection. Our 15-parameter camera model is of much lower dimensionality than camera array models, and more closely represents the physics of lenselet-based cameras. Results include calibration of a commercially available camera using three calibration grid sizes over five datasets. Typical RMS ray reprojection errors are 0.0628, 0.105 and 0.363 mm for 3.61, 7.22 and 35.1 mm calibration grids, respectively. Rectification examples include calibration targets and real-world imagery.
In this paper we undertake a systematic investigation of affine invariant object detection. Edge detection is first presented from the point of view of the affine invariant scale-space obtained by curvature based moti...
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ISBN:
(纸本)0818672587
In this paper we undertake a systematic investigation of affine invariant object detection. Edge detection is first presented from the point of view of the affine invariant scale-space obtained by curvature based motion of the image level-sets. In this case, affine invariant edges are obtained as a weighted difference of images at different scales. We then introduce the affine gradient as the simplest possible affine invariant differential function which has the same qualitative behavior as the Euclidean gradient magnitude. These edge detectors are the basis both to extend the affine invariant scale-space to a complete affine flow for image denoising and simplification, and to define affine invariant active contours for object detection and edge integration. The active contours are obtained as a gradient flow in a conformally Euclidean space defined by the image on which the object is to be detected. That is, we show that objects can be segmented in an affine invariant manner by computing a path of minimal weighted affine distance, the weight being given by functions of the affine edge detectors. The geodesic path is computed via an algorithm which allows to simultaneously detect any number of objects independently of the initial curve topology.
A new exemplar-based framework unifying image completion, texture synthesis and image inpainting is presented in this work. Contrary to existing greedy techniques, these tasks are posed in the form of a discrete globa...
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The demo presents a virtual min-or interface which reacts to the viewer using robust, real-time face tracking. The display directly combines a user's face with various graphical distortions, performed only on the ...
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ISBN:
(纸本)0818684976
The demo presents a virtual min-or interface which reacts to the viewer using robust, real-time face tracking. The display directly combines a user's face with various graphical distortions, performed only on the face region in the image. The face detection and tracking is done in real-time, so the graphical effect stays with the user and continues to adapt as they move within the viewing space, increasing in intensity as the user approaches the display.
The silhouette of a smooth 3D object observed by a moving camera changes over time. Past work has shown how surface geometry can be recovered using the deformation of the silhouette when the camera motion is known. Th...
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ISBN:
(纸本)0818672587
The silhouette of a smooth 3D object observed by a moving camera changes over time. Past work has shown how surface geometry can be recovered using the deformation of the silhouette when the camera motion is known. This paper addresses the problem of estimating both the full Euclidean surface structure and the camera motion from a dense set of silhouettes captured under orthographic or scaled orthographic projection. The approach relies on a viewpoint-invariant representation of curves swept by viewpoint-dependent features such as bitangents, inflections and contour points with parallel tangents. Feature points, which form stereo frontier points between non-consecutive images, are matched using this representation. The camera's angular velocity is computed from constraints derived from this correspondence along with the image velocity of these features. From the angular velocity, the epipolar geometry is ascertained, and infinitesimal motion frontier points can be detected. In turn, the motion of these frontier points constrains the translation component of camera motion. Finally, the surface is reconstructed using established techniques once the camera motion has been estimated.
A combination of techniques that is becoming increasingly popular is the construction of part-based object representations using the outputs of interest-point detectors. Our contributions in this paper are twofold: fi...
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The computation of relations from a number of potential matches is a major task in computervision. Often RANSAC is employed for the robust computation of relations such as the fundamental matrix. For (quasi-)degenera...
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We consider the problem of feature-based face recognition in the setting where only a single example of each face is available for training. The mixture-distance technique we introduce achieves a recognition rate of 9...
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ISBN:
(纸本)0818672587
We consider the problem of feature-based face recognition in the setting where only a single example of each face is available for training. The mixture-distance technique we introduce achieves a recognition rate of 95% on a database of 685 people in which each face is represented by 30 measured distances. This is currently the best recorded recognition rate for a feature-based system applied to a database of this size. By comparison, nearest neighbor search using Euclidean distance yields 84%. In our work a novel distance function is constructed based on local second order statistics as estimated by modeling the training data as a mixture of normal densities. We report on the results from mixtures of several sizes. We demonstrate that a flat mixture of mixtures performs as well as the best model and therefore represents an effective solution to the model selection problem. A mixture perspective is also taken for individual Gaussians to choose between first order (variance) and second order (covariance) models. Here an approximation to flat combination is proposed and seen to perform well in practice. Our results demonstrate that even in the absence of multiple training examples for each class, it is sometimes possible to infer from a statistical model of training data, a significantly improved distance function for use in patternrecognition.
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