We address the problem of integrating multi-frame stereo and shading cues within the framework of optimization in the infinite-dimensional space of piecewise smooth surfaces. Cue integration then reduces to the determ...
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ISBN:
(纸本)0769506623
We address the problem of integrating multi-frame stereo and shading cues within the framework of optimization in the infinite-dimensional space of piecewise smooth surfaces. Cue integration then reduces to the determination of regions where prior assumptions on the reflectance of the surfaces can be enforced. By combining cues, our formulation allows defining a well-posed problem even when reconstruction from stereo or shading in isolation would be ill-posed. For a simplified model we prove the necessary conditions for optimality, and propose an iterative optimization algorithm, which we implement using ultra-narrowband level set methods.
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.
Three different statistical models of colour data for use in segmentation or tracking algorithms are proposed. Results of a performance comparison of a tracking algorithm, applied to two separate applications, using e...
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ISBN:
(纸本)0780342364
Three different statistical models of colour data for use in segmentation or tracking algorithms are proposed. Results of a performance comparison of a tracking algorithm, applied to two separate applications, using each of the three different types of underlying model of the data are presented. From these a comparison of the performance of the statistical colour models themselves is obtained.
We present a new, efficient stereo algorithm addressing robust disparity estimation in the presence of occlusions. The algorithm is an adaptive, multi-window scheme using left-right consistency to compute disparity an...
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ISBN:
(纸本)0780342364
We present a new, efficient stereo algorithm addressing robust disparity estimation in the presence of occlusions. The algorithm is an adaptive, multi-window scheme using left-right consistency to compute disparity and its associated uncertainty. We demonstrate and discuss performances with both synthetic and real stereo pairs, and show how our results improve an those of closely related techniques for both robustness and efficiency.
This paper presents a robust and accurate vision-based augmented reality system for surgical navigation. The key point of our system is a robust and real-time monocular vision algorithm to estimate the 3D pose of surg...
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This paper presents a robust and accurate vision-based augmented reality system for surgical navigation. The key point of our system is a robust and real-time monocular vision algorithm to estimate the 3D pose of surgical tools, utilizing specially designed code markers and Kalman filter-based position updating. The vision system is not impaired by occlusion and rapid change of illumination. The augmented reality system superimposes the 3D object wireframe onto the live viewing image taken from the surgical microscope as well as displaying other useful navigation information, while allowing the surgeons to freely change its room and focus for viewing. The experimental results verified the robustness and usefulness of the system, and acquired the image registration error less than 2 mm.
We present an approach to appearance-based object recognition using single camera images. Our approach is based on using an attention mechanism to obtain visual features that are generic, robust and informative. The f...
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ISBN:
(纸本)0769506623
We present an approach to appearance-based object recognition using single camera images. Our approach is based on using an attention mechanism to obtain visual features that are generic, robust and informative. The features themselves are recognized using principal components in the frequency domain. In this paper we show how the visual characteristics of only a small number of such features can be used for appearance-based object recognition that is not confounded by planar rotations or background clutter.
In this paper;a robust patternrecognition system, using an appearance-based representation of colour images is described. Standard appearance-based approaches are not robust to outliers, occlusions or segmentation er...
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ISBN:
(纸本)0769506623
In this paper;a robust patternrecognition system, using an appearance-based representation of colour images is described. Standard appearance-based approaches are not robust to outliers, occlusions or segmentation errors. The approach proposed here relies on robust M-estimators, involving non-quadratic and possibly non-convex energy functions. To deal with the minimisation of non-convex functions in a deterministic framework, we introduce an estimation scheme relying on M-estimators used in continuation, from convex functions to hard redescending nonconvex estimators. At each step of the robust estimation scheme, the non-quadratic criterion is minimized using the half-quadratic theory. This leads to a weighted least squares algorithm, which is easy to implement. The proposed robust estimation scheme does not require any user interaction because all necessary parameters are previously estimated. The method is illustrated on a road sign recognition application. Experiments show significant improvements with respect to standard estimation schemes.
We develop methods to extract semantically meaningful symmetries from color images. These symmetries are defined within and between color hands using complex moments computed from the output of a bank of orientation a...
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ISBN:
(纸本)0780342364
We develop methods to extract semantically meaningful symmetries from color images. These symmetries are defined within and between color hands using complex moments computed from the output of a bank of orientation and scale selective filters. From this representation, we derive a set of features which are invariant to rotation, scale, and illumination a conditions. Experimental results are provided to show the performance of this set of features for classification and image database partitioning.
Unconstrained illumination and pose variation lead to significant variation in the photographs of faces and constitute a major hurdle preventing the widespread use of face recognition systems. The challenge is to gene...
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Unconstrained illumination and pose variation lead to significant variation in the photographs of faces and constitute a major hurdle preventing the widespread use of face recognition systems. The challenge is to generalize from a limited number of images of an individual to a broad range of conditions. Recently, advances in modeling the effects of illumination and pose have been accomplished using three-dimensional (3-D) shape information coupled with reflectance models. Notable developments in understanding the effects of illumination include the nonexistence of illumination invariants, a characterization of the set of images of objects in fixed pose under variable illumination (the illumination cone), and the introduction of spherical harmonics and low-dimensional linear subspaces for modeling illumination. To generalize to novel conditions, either multiple images must be available to reconstruct 3-D shape or, if only a single image is accessible, prior information about the 3-D shape and appearance of faces in general must be used. The 3-D Morphable Model was introduced as a generative model to predict the appearances of an individual while using a statistical prior on shape and texture allowing its parameters to be estimated from single image. Based on these new understandings, face recognition algorithms have been developed to address the joint challenges of pose and lighting. in this paper, we review these developments and provide a brief survey of the resulting face recognition algorithms and their performance.
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