Reconstructing 3D scenes with independently moving objects from uncalibrated monocular image sequences still poses serious challenges. One important problem is to find the relative scales between these different recon...
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Reconstructing 3D scenes with independently moving objects from uncalibrated monocular image sequences still poses serious challenges. One important problem is to find the relative scales between these different reconstructed objects. The perspective reconstruction of a single object can only be known up to a certain scale which results in a one-parameter family of relative scales and trajectories per moving object. The paper formulates this ambiguity and proposes solutions in the vein of "non-accidentalness". Two instantiations of its use are analyzed: planar motion and the 'heading constraint'.
We present an adaptive three-mode PCA framework for recognizing gender from walking movements. Prototype female and male walkers are initially decomposed into a sub-space of their three-mode components (posture, time,...
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We present results on the latest advances in thermal infrared face recognition, and its use in combination with visible imagery. Previous research by the authors has shown high performance under very controlled condit...
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We present results on the latest advances in thermal infrared face recognition, and its use in combination with visible imagery. Previous research by the authors has shown high performance under very controlled conditions, or questionable performance under a wider range of conditions. This paper shows results on the use of thermal infrared and visible imagery for face recognition in operational scenarios. In particular, we show performance statistics for outdoor face recognition and recognition across multiple sessions. Our results support the conclusion that face recognition performance with thermal infrared imagery is stable over multiple sessions, and that fusion of modalities increases performance. As measured by the number of images and number of subjects, this is the largest ever reported study on thermal face recognition.
This paper presents a novel affine registration algorithm for diffusion tensor images. The proposed metric derived from the standpoint of diffusion profiles not only has concrete physical underpinning but also can be ...
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This paper presents a novel affine registration algorithm for diffusion tensor images. The proposed metric derived from the standpoint of diffusion profiles not only has concrete physical underpinning but also can be extended for comparing higher-order diffusion models. The non-translauonal part of the affine transformation is parametrized in the spirit of the Polar Decomposition Theorem. The registration objective function and its derivatives are derived analytically by combining this parametrization scheme with finite strain tensor reorientation. The affine algorithm is embeded in a multi-resolution piecewise affine framework for non-rigid registration.
Various facial region biometrics have been used extensively in the areas of recognition and authentication. However, some regions of the face provide more information than is currently being fully utilized in these sp...
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We present new binomial models of open- and closed-set identification recognition performance, giving formulae for identification and false match rates as functions of database size, match rank and operating threshold...
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We present new binomial models of open- and closed-set identification recognition performance, giving formulae for identification and false match rates as functions of database size, match rank and operating threshold. We compare these with previously published models and with results from face recognition trials on populations of size 4 104. We note verification to be a special case of open-set identification and relate area under the receiver operating characteristic to closed-set identification. We find the binomial model approximates performance at low false match rates but underestimates identification rates on closed sets. We implicate the binomial iid assumption, but show conditioning and score transformation methods that ameliorate this.
In this paper, an automatic system is presented to establish databases for face recognition from video. We propose a temporal-based face detector, which can improve the detection rate as well as the recognition rate w...
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We present a novel method for automatic fingerspelling recognition which is able to discriminate complex hand configurations with high amounts of finger occlusions. Such a scenario, while common in most fingerspelling...
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Information obtained from calibrated cameras by means of computervision is integrated with location events from an ultrasonic tracking system deployed in an indoor office. This results in improved estimates of state ...
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Underwater imaging is important for scientific research and technology, as well as for popular activities. We present a computervision approach which easily removes degradation effects in underwater vision. We analyz...
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Underwater imaging is important for scientific research and technology, as well as for popular activities. We present a computervision approach which easily removes degradation effects in underwater vision. We analyze the physical effects of visibility degradation. We show that the main degradation effects can be associated with partial polarization of light. We therefore present an algorithm which inverts the image formation process, to recover a good visibility image of the object The algorithm is based on a couple of images taken through a polarizer at different orientations. As a by product, a distance map of the scene is derived as well. We successfully used our approach when experimenting in the sea using a system we built. We obtained great improvement of scene contrast and color correction, and nearly doubled the underwater visibility range.
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