We derive a sensitivity analysis for moment invariants of multidimensional distributions, These invariants have many uses in computational systems and have recently been used for illumination-invariant recognition in ...
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ISBN:
(纸本)0780342364
We derive a sensitivity analysis for moment invariants of multidimensional distributions, These invariants have many uses in computational systems and have recently been used for illumination-invariant recognition in color images. In this context, the sensitivity analysis predicts the response of moment invariants to partial occlusion. Using the results of the sensitivity analysis, we develop a novel surface representation called the invariant profile which captures color distribution and spatial information while remaining invariant to the spectral content of the scene illumination. Unlike previous representations, the recognition of invariant profiles does not require illumination correction. We demonstrate the sensitivity analysis and the use of invariant profiles for recognition with a set of experiments on color images.
This paper presents a robust technique to detect local deteriorations of old cinematographic films. This method relies on spatio-temporal information and combines two different detectors : a morphological detector whi...
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ISBN:
(纸本)0780342364
This paper presents a robust technique to detect local deteriorations of old cinematographic films. This method relies on spatio-temporal information and combines two different detectors : a morphological detector which uses spatial properties of deteriorations, and a dynamic detector based on motion estimation techniques. Our deterioration detector has been validated Olt several film sequences and turned out to be a powerful tool for digital film restoration.
We present a new method for synthesizing novel views of a 3D scene from few model images in full correspondence. The core of this work is the derivation of a tensorial operator that describes the transformation from) ...
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ISBN:
(纸本)0780342364
We present a new method for synthesizing novel views of a 3D scene from few model images in full correspondence. The core of this work is the derivation of a tensorial operator that describes the transformation from) a given tensor of three views to a novel tensor of a new configuration of three views. BL repeated application of the operator an a seed tensor with a sequence of desired virtual camera positions we obtain a chain of warping functions (tensors) from the set of model images to create the desired virtual views.
Previous work [5], [2] have developed an approach for estimating shape and albedo from multiple images assuming Lambertian reflectance with single light sources. The main contributions of this paper are: (i) to show h...
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ISBN:
(纸本)0780342364
Previous work [5], [2] have developed an approach for estimating shape and albedo from multiple images assuming Lambertian reflectance with single light sources. The main contributions of this paper are: (i) to show how the approach can be generalized to include ambient background illumination, (ii) to demonstrate the use of the integrability constraint for solving this problem, and (iii) an iterative algorithm which is able to improve the analysis by finding shadows and rejecting them.
The general problem of surface matching is considered in this study. The process described in this work hinges on a geodesic distance equation for a family of surfaces embedded in the graph of a cost function. The cos...
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ISBN:
(纸本)0769506623
The general problem of surface matching is considered in this study. The process described in this work hinges on a geodesic distance equation for a family of surfaces embedded in the graph of a cost function. The cost function represents the geometrical matching criterion between the two 3D surfaces. This graph is a hypersurface in 4-dimensional space, and the theory presented herein is a generalization of the geodesic curve evolution method introduced by R. Kimmel et al [10] it also generalizes the 2D matching process developed in [4]. An Eulerian level-set formulation of the geodesic surface evolution is also used, leading to a numerical scheme for solving partial differential equations originating from hyperbolic conservation laws [14] which has proven to be very robust and stable. The method is applied on examples showing both small and large deformations, and arbitrary topological changes.
We propose a new method for view synthesis from real images using stereo vision. The method does not explicitly model scene geometry, and enables fast and exact generation of synthetic views. We also reevaluate the re...
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ISBN:
(纸本)0818672587
We propose a new method for view synthesis from real images using stereo vision. The method does not explicitly model scene geometry, and enables fast and exact generation of synthetic views. We also reevaluate the requirements on stereo algorithms for the application of view synthesis and discuss ways of dealing with partially occluded regions of unknown depth and with completely occluded regions of unknown texture. Our experiments demonstrate that it is possible to efficiently synthesize realistic new views even from inaccurate and incomplete depth information.
A local parallel method is described for computing the stochastic completion field introduced in an earlier report. The local parallel method can be interpreted as a stable finite difference scheme for solving the und...
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ISBN:
(纸本)0818672587
A local parallel method is described for computing the stochastic completion field introduced in an earlier report. The local parallel method can be interpreted as a stable finite difference scheme for solving the underlying Fokker-Planck equation identified by Mumford. The new method is more plausible as a neural model since (1) unlike the previous method, it can be computed in a sparse, locally connected network;and (2) the network dynamics are consistent with psycophysical measurements of the time course of illusory contour formation.
We explore the task of recognizing peoples' identities in photo albums in an unconstrained setting. To facilitate this, we introduce the new People In Photo Albums (PIPA) dataset, consisting of over 60000 instance...
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ISBN:
(纸本)9781467369640
We explore the task of recognizing peoples' identities in photo albums in an unconstrained setting. To facilitate this, we introduce the new People In Photo Albums (PIPA) dataset, consisting of over 60000 instances of similar to 2000 individuals collected from public Flickr photo albums. With only about half of the person images containing a frontal face, the recognition task is very challenging due to the large variations in pose, clothing, camera viewpoint, image resolution and illumination. We propose the Pose Invariant PErson recognition (PIPER) method, which accumulates the cues of poselet-level person recognizers trained by deep convolutional networks to discount for the pose variations, combined with a face recognizer and a global recognizer. Experiments on three different settings confirm that in our unconstrained setup PIPER significantly improves on the performance of DeepFace, which is one of the best face recognizers as measured on the LFW dataset.
Current methods for registering image regions perform well for simple transformations or large image regions. In this paper, we present a new method that is better able to handle small image regions as they deform wit...
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ISBN:
(纸本)0780342364
Current methods for registering image regions perform well for simple transformations or large image regions. In this paper, we present a new method that is better able to handle small image regions as they deform with non-linear transformations. We introduce difference decompositon, a novel approach to solving the registration problem. The method is a generalization of previous methods and can better handle non-linear transforms. Although the methods are general, we focus on projective transformations and introduce piecewise-projective transformations for modeling the motions of non-planar objects. We conclude with examples from our prototype implementation.
We develop a simple and very fast method for object tracking based exclusively on color information in digitized video images. Running on a Silicon Graphics R4600 Indy system with an IndyCam, our algorithm is capable ...
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ISBN:
(纸本)0780342364
We develop a simple and very fast method for object tracking based exclusively on color information in digitized video images. Running on a Silicon Graphics R4600 Indy system with an IndyCam, our algorithm is capable of simultaneously tracking objects at full frame size (640 x 480 pixels) and video frame rate (30 fps). Robustness with respect to occlusion is achieved via an explicit hypothesis-tree model of the occlusion process. We demonstrate the efficacy of our technique in the challenging task of tracking people, especially tracking human heads and hands.
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