A robust, multi-frame, progressive refinement framework for registering narrow field of view video to reference imagery is presented. A major strength of the approach is its effectiveness in the presence of dissimilar...
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ISBN:
(纸本)0769512720
A robust, multi-frame, progressive refinement framework for registering narrow field of view video to reference imagery is presented. A major strength of the approach is its effectiveness in the presence of dissimilar video and reference image appearance. Normalized oriented energy image pyramids are employed to enable alignment of images with global visual dissimilarities, yet local feature commonality. Local matching is then applied coarse-to-fine along four dimensions: spatial frequency, local support, search range, and model order - a robust parametric model fit is used to reject outliers at each iteration. Globally optimal multi-frame alignment is obtained with respect to several constraints: frame-to-reference local matches, recovered frame-to-frame motion, and optional a priori estimates of sensor pose. The framework is described in detail and applied to two examples: aerial video to geographic reference image alignment (georegistration) and retinal slit lamp video to fundus image alignment.
The proceedings contains 158 papers from 2001 ieeecomputersocietyconference on computer vision and patternrecognition. The topics discussed include: image indexing, image segmentation, computer vision, image codin...
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The proceedings contains 158 papers from 2001 ieeecomputersocietyconference on computer vision and patternrecognition. The topics discussed include: image indexing, image segmentation, computer vision, image coding, patternrecognition systems, image magnification, video inpainting, visual tracking, motion estimation, face recognition, imaging systems, character recognition and feature clustering.
A robust approach for super resolution is presented, which is especially valuable in the presence of outliers. Such outliers may be due to motion err-os, inaccurate blur models, noise, moving objects, motion blur etc....
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ISBN:
(纸本)0769512720
A robust approach for super resolution is presented, which is especially valuable in the presence of outliers. Such outliers may be due to motion err-os, inaccurate blur models, noise, moving objects, motion blur etc. This robustness is needed since super-resolution methods are very sensitive to such errors. A robust median estimator is combined in an iterative process to achieve a super resolution algorithm. This process can increase resolution even in regions with outliers, where other super. resolution methods actually degrade the image.
In this paper, we present a segmented linear subspace model for face recognition that is robust under varying illumination conditions. The algorithm generalizes the 3D illumination subspace model by segmenting the ima...
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In this paper, we present a segmented linear subspace model for face recognition that is robust under varying illumination conditions. The algorithm generalizes the 3D illumination subspace model by segmenting the image into regions that have surface normals whose directions are close to each other. This segmentation is performed using a K-means clustering algorithm and requires only a few training images under different illuminations. When the linear subspace model is applied to the segmented image, recognition is robust to attached and cast shadows, and the recognition rate is equal to that of computationally more complex systems that require constructing the 3D surface of the face.
We present an efficient grouping strategy for the detection of regular repetitions of planar (but not necessarily coplanar) patterns. At the heart of our system lie the fixed structures that typify the geometric trans...
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ISBN:
(纸本)0769512720
We present an efficient grouping strategy for the detection of regular repetitions of planar (but not necessarily coplanar) patterns. At the heart of our system lie the fixed structures that typify the geometric transformations of the regularities. The approach unifies a number of grouping types that have traditionally been dealt with separately. It avoids the use of combinatorics in the search for pattern repetitions, through the combined use of invariants for hashing-based pattern matching on the one hand, and Hough transforms for the detection of the fixed structures on the other hand. In this paper we concentrate on planar homologies and elations in particular. Results on real-world scenes demonstrate the performance of the approach.
In this paper, we present an efficient method to synthesize large-scale scenes, such as broad city landscapes. To date, model based approaches have mainly been adopted for this purpose, and some fairly convincing poly...
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ISBN:
(纸本)0769512720
In this paper, we present an efficient method to synthesize large-scale scenes, such as broad city landscapes. To date, model based approaches have mainly been adopted for this purpose, and some fairly convincing polygon cities have been successfully generated. However, the shapes of real world objects are usually very complicated and it is infeasible to model an entire city realistically. On the other hand, image based approaches have been attempted only recently. image based methods are effective for realistic rendering, but their huge data sets and restrictions on interactivity pose serious problems for an actual application. Thus, we propose a hybrid method, which uses simple shapes such as planes to model the city, and applies image based techniques to add realism. It can be performed automatically through a simple image capturing process. Further, We also analyze the relationship between error and number of needed images to reduce the data size.
This paper presents a novel processing.scheme for the automatic computation of a medial shape model which is representative for an object population with shape variability. The sensitivity of medial descriptions to ob...
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ISBN:
(纸本)0769512720
This paper presents a novel processing.scheme for the automatic computation of a medial shape model which is representative for an object population with shape variability. The sensitivity of medial descriptions to object variations and small boundary perturbations are fundamental problems of any skeletonization technique. These problems are approached with the computation of a model with common medial branching topology and grid sampling. This model is then used for a medial shape description of individual objects via a constrained model fit. The process starts from parametric 3D boundary representations with existing point-to-point homology between objects. The Voronoi diagram of each sampled object boundary is grouped into medial sheets and simplified by a pruning algorithm using a volumetric contribution criterion. Medial sheets are combined to form a common medial branching topology. Finally, the medial sheets are sampled and represented as meshes of medial primitives. We present new results on populations of up to 184 biological objects. For these objects the common medial branching topology is described by a small number of sheets. Despite the coarse medial sampling, a close approximation of individual objects is achieved.
Many recent content-based image retrieval techniques utilize relevance feedback (RF) from the user to adjust the system response to better meet user expectations. One school of RF-based methods uses a weighted Minkows...
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ISBN:
(纸本)0769512720
Many recent content-based image retrieval techniques utilize relevance feedback (RF) from the user to adjust the system response to better meet user expectations. One school of RF-based methods uses a weighted Minkowski distance metric to assess similarity, and adjusts the weights to refine query response. A new method of estimating these weight vectors is presented which outperforms existing methods, particularly for the important case of limited training data. A new objective function is presented for an iterative optimization routine which more closely aligns optimization goals with true system goals. A new analysis framework is presented in the derivation of this technique which is useful for understanding the limitations of many RF methods.
This paper presents a natural extension of the newly introduced "anti-face" method to event detection, both in the image and in the feature domains In the case of the image domain (video sequences) we mate s...
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ISBN:
(纸本)0769512720
This paper presents a natural extension of the newly introduced "anti-face" method to event detection, both in the image and in the feature domains In the case of the image domain (video sequences) we mate spatio-temporal templates by stacking the video frames, and the detection is performed on these templates. In order to recognise the motion of features in a video sequence, the spatial locations of the features are modulated in time, thus creating a one-dimensional vector which represents the event. The following applications of anti-sequences are presented. 1) Detection of an oiled under 3D rotations in a video sequence simulated from the COIL database, 2) Visual speech recognition of spoken words, and 3) recognition of symbols sketched with a laser pointer. The resulting detection algorithm is very fast, and is robust enough to work on small images. Also, it is capable of discriminating the desired event-template from arbitrary events, and not only events in a "negative training set".
Color histograms are a central feature in many image retrieval systems. Indeed they are part of the MPEG-7 standard. But histograms suffer from the "curse of dimensionality" in which the number of bins incre...
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ISBN:
(纸本)0769512720
Color histograms are a central feature in many image retrieval systems. Indeed they are part of the MPEG-7 standard. But histograms suffer from the "curse of dimensionality" in which the number of bins increases exponentially with the number of dimensions. There is therefore an imperative for methods for simplifying histograms. This paper presents a new method for simplifying histograms based on a cascade of increasing-scale graph morphology filters. The system we choose preserves scale space causality and so preserves the modes of the histogram. The method is quick to compute so is therefore a practically useful feature. We present results using the MPEG-7 Common Color Dataset that show that these new compressed features have a retrieval performance that is equivalent to full histograms.
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