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Many algorithms for the computation of correspondences between deformable shapes rely on some variant of nearest neighbor matching in a descriptor space. Such are, for example, various point-wise correspondence recovery algorithms used as a post-processing stage in the functional correspondence framework. Such frequently used techniques implicitly make restrictive assumptions (e.g., nearisometry)...
A minimal solution using two affine correspondences is presented to estimate the common focal length and the fundamental matrix between two semi-calibrated cameras – known intrinsic parameters except a common focal length. To the best of our knowledge, this problem is unsolved. The proposed approach extends point correspondence-based techniques with linear constraints derived from local...
Estimating human pose, shape, and motion from images and videos are fundamental challenges with many applications. Recent advances in 2D human pose estimation use large amounts of manually-labeled training data for learning convolutional neural networks (CNNs). Such data is time consuming to acquire and difficult to extend. Moreover, manual labeling of 3D pose, depth and motion is impractical. In...
In this work we pursue a data-driven approach to the problem of estimating surface normals from a single intensity image, focusing in particular on human faces. We introduce new methods to exploit the currently available facial databases for dataset construction and tailor a deep convolutional neural network to the task of estimating facial surface normals in-the-wild. We train a fully convolutional...
This paper tackles the problem of estimating 3D human poses from given 2D landmarks, which is still an ill-posed problem. The existing works have successfully applied Active Shape Model approach to estimate 3D human poses, but the error is still high. In this paper, we propose an improved method by using the cascade of neural networks to make the estimated shape more alike to the ground truth shape...
Multi-view stereo relies on feature correspondences for 3D reconstruction, and thus is fundamentally flawed in dealing with featureless scenes. In this paper, we propose polarimetric multi-view stereo, which combines per-pixel photometric information from polarization with epipolar constraints from multiple views for 3D reconstruction. Polarization reveals surface normal information, and is thus helpful...
Videos for outdoor scene often show unpleasant blur effects due to the large relative motion between the camera and the dynamic objects and large depth variations. Existing works typically focus monocular video deblurring. In this paper, we propose a novel approach to deblurring from stereo videos. In particular, we exploit the piece-wise planar assumption about the scene and leverage the scene flow...
The optical flow of natural scenes is a combination of the motion of the observer and the independent motion of objects. Existing algorithms typically focus on either recovering motion and structure under the assumption of a purely static world or optical flow for general unconstrained scenes. We combine these approaches in an optical flow algorithm that estimates an explicit segmentation of moving...
Given a single photo of a room and a large database of furniture CAD models, our goal is to reconstruct a scene that is as similar as possible to the scene depicted in the photograph, and composed of objects drawn from the database. We present a completely automatic system to address this IM2CAD problem that produces high quality results on challenging imagery from interior home design and remodeling...
With the rapid development of Remote Sensing acquisition techniques, there is a need to scale and improve processing tools to cope with the observed increase of both data volume and richness. Among popular techniques in remote sensing, Deep Learning gains increasing interest but depends on the quality of the training data. Therefore, this paper presents recent Deep Learning approaches for fine or...
We proposed a novel blind polarization de-multiplexing technique for higher order modulation signals based on unscented Kalman filter (UKF) in 3D Stokes space. Simulation results show that UKF has better performance of de-multiplexing and convergence speed compared to extended Kalman filters (EKF).
TomoSAR provides 3D information of complex targets such as forests. Space-borne SAR data utility for TomoSAR analysis is limited due to temporal decorrelation. A novel technique is introduced which utilizes multiple TanDEM-X data sets to generate accurate tomograms. The technique is demonstrated using multiple space-borne SAR acquisitions over Indian tropical forest. Cross-validation with PolInSAR...
In this paper, we introduce two spatially adaptive covariance filtering methods and evaluate their effect on scatterer separation and height estimation from tomographic SAR. The first one was previously introduced for polarimetric data and uses pixel similarities based on Riemannian distances between covariance matrices. The second one is a new method extending the previous one to patch-based similarities...
A novel 3D image-based indoor localization system integrated with an obstacle removal component is proposed. In contrast with existing state-of-the-art localization techniques focusing on static outdoor or indoor environments, the adverse effects generated by moving obstacles, which are very common in busy indoor spaces, is considered in our work. In particular, this problem is converted into a separation...
The article concerns the automatic calibration of a camera with radial distortion from a single image. It is known that, under the mild assumption of square pixels and zero skew, lines in the scene project into circles in the image, and three lines suffice to calibrate the camera up to an ambiguity between focal length and radial distortion. The calibration results highly depend on accurate circle...
Allowing for a priori optimization of the robot manipulation to improve the performance in the unmanned environment, it is critical for the augmented reality system to estimate the attitude of point clouds in model reconstruction. The estimation of planar parameter is not always faithful for point cloud fitting, because the gross errors and outliers are not considered in by the traditional plane fitting...
In this paper, a novel closed-form transformation estimation method based on feature guided moving least squares together with manifold regularization is proposed for nonrigid image/surface deformation. The method takes the user-controlled point-offset-vectors and the feature points of the image/surface as input, and estimates the spatial transformation between the two control point sets for each...
Eye gaze is an important non-verbal cue for human affect analysis. Recent gaze estimation work indicated that information from the full face region can benefit performance. Pushing this idea further, we propose an appearance-based method that, in contrast to a long-standing line of work in computer vision, only takes the full face image as input. Our method encodes the face image using a convolutional...
Three-dimensional surface reconstruction based on photometric stereo requires accurate positioning of the light source or estimation of the lighting parameters, which increases the complexity of the operation in experiments. Moreover, the actual light environment is composed of many kinds of complex optical components, and the accurate lighting parameters cannot be measured. In this paper, a reference...
In this work we present how 3-dimensional ferroelectric domains observed in MAPbIs affect the performance of perovskite solar cells. We simulated a 3D system with dimensions of 500 nm × 500 nm × 300 nm, considering domains with 100 nm side length which have been assigned random orientations of the polarization field. Calculations are performed with the simulator TiberCAD using a 3D drift-diffusion...
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