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In cardiac gated SPECT, image reconstruction suffers from several degrading factors including limited data counts, depth-dependent blur, attenuation, scatter, and motion blur. In our recent work it was demonstrated that use of motion-compensated temporal processing could lead to improved accuracy in 4D reconstruction. In this work we investigate how different optical flow estimation methods can affect...
High-level vision applications often incorporate image segmentation techniques into their preprocessing stages to reduce image data and to improve overall execution efficiency. Traditional segmentation approaches often focus on creating homogenous, connected regions of pixels to roughly correspond with image object boundaries. These methods tend to blend or remove important image details and are often...
In order to overcome the shortcomings of the shape from shading (SFS) algorithm in items of clearness and smoothness of silhouette in reconstructed objects, a modified SFS algorithm is proposed in this paper. Firstly, we determine the primary factors affecting reconstruction by analyzing the Lambertian light reflection model. Secondly, we perform image restoration and background smoothing by extracting...
In multi-view stereo setting, pixel correspondence problem and super resolution problem are inter-related in a sense that the result of each problem could help to solve the other. In this paper, we propose a novel method to solve two problems together by optimizing a unified energy functional. Main difference from the previous works is that the consistency between high resolution images is considered...
Geometric reconstruction from image collections is a classical computer vision problem. The problem essentially consists of two steps; First, the identification of matches and assembling of point tracks, and second, multiple view geometry computations. In this paper we address the problem of constructing point tracks using graph theoretical algorithms. From standard descriptor matches between all...
Local Binary Descriptors (LBDs) are good at matching image parts, but how much information is actually carried? Surprisingly, this question is usually ignored and replaced by a comparison of matching performances. In this paper, we directly address it by trying to reconstruct plausible images from different LBDs such as BRIEF [4] and FREAK [1]. Using an inverse problem framework, we show that this...
This paper presents a new stereo-motion approach for 3D scene reconstruction in dense and accurate form, that allows the cameras to be described by the full perspective model. Given a short and arbitrary motion of a stereo rig of camera, the projective depth of every image point can be recovered from the rank-four property of a matrix that comprises the image positions of the scene, and the associated...
Holistic scene understanding is a major goal in recent research of computer vision. To deal with this task, reasoning the 3D relationship of components in a scene is identified as one of the key problems. We study this problem in terms of structural reconstruction of 3D scene from single view image. Our first step concentrates on geometrical layout analysis of scene using low-level features. We allocate...
Given a single image of a scene rectangle of an unknown aspect ratio and size, we present a method to reconstruct the projective structure and to find camera parameters including focal length, position, and orientation. First, we solve the special case when the center of a scene rectangle is projected to the image center. We formulate this problem with coupled line cameras and present the analytic...
Given a set of high-resolution images of a scene, it is often desirable to predict the scene's appearance from viewpoints not present in the original data for purposes of change detection. When significant 3-D relief is present, a model of the scene geometry is necessary for accurate prediction to determine surface visibility relationships. In the absence of an a priori high-resolution model (such...
3D human face modeling has been a persistent challenge in both computer vision and computer graphics. Face modeling refers to modeling the 3D geometry of static or non-static human faces which lays the foundation for model based face analysis and facial animations. In this paper we have surveyed the various methods available for generating 3D human face models. Currently, the 3D face models can be...
The 3D reconstruction of buildings is a challenging research problem especially for image-based methods due to the absence of textured surfaces and difficulty in detecting high-level architectural structures. In this paper, we present an image-based reconstruction algorithm for efficiently modeling of buildings with the Manhattan-world assumption. The first key component of the algorithm is a clustering...
In the present position paper, I formulate some (in part critical) remarks related to some techniques which are successfully used in contemporary live dense reconstruction approaches. Main issues are feature based correspondence vs. image-based matching, the generalization of the brightness constancy assumption, and the handling of featureless regions which do not allow direct determination of correspondence.
In this paper, we propose an efficient people localization approach using multiple cameras based on axial representations of foreground regions. Unlike many previous methods that need to project all foreground pixels of all views to multiple reference planes via homography, we instead apply vanishing point-based line sampling to reduce the large amount of pixel processing so that computational efficiency...
This paper introduces a novel method for 3D reconstruction from spherical mirrors in a single view. Traditional reconstruction algorithms either assume both intrinsic and extrinsic parameters of the cameras being known precisely and rely on multiple view information to recover 3D objects, or use reflections of the 3D objects on spherical mirrors with known radii in a single calibrated view. It will...
Recently we investigated the use of a Fourier harmonic model for determining the optical flow in a periodic image sequence, the goal of which was to exploit the temporal continuity and periodicity in the underlying motion field. In this work, we further develop this optical flow model by incorporating a spatially piecewise smoothness constraint (in the form of total variation) in order to better accommodate...
Shape from shading (SFS) is one of the most fundamental problems in Computer Vision: reconstruction of the three-dimensional (3D) shape of photographed objects given a single input image. Image formation is then modelled based on assumptions on illumination and light reflectance. Solving the 3D shape from the model is useful for many applications. SFS has been extended, for example, to several input...
In this paper we investigate the challenge of 3D reconstruction from Snooker video data. We propose a system pipeline for intelligent filtering based on semantic importance in Snooker. The system can be divided into table detection and correction, followed by ball detection, classification and tracking. It is apparent from previous work that there are several challenges presented here. Firstly, previous...
In this paper, we reconstruct 3D shape from a single image. We use level set method to solve the Eikonal equation which can obtained from the method of shape from shading (SFS). However, the results are not usually usable due to the concave-convex ambiguity problems inherent to SFS, so we find out the boundary of the concave-convex ambiguities according to the flatness of the triangle faces and use...
We propose an algorithm for finding out the single or multiple camera calibration planar coded patterns from an image with a complicate background, and provide a kind of patterns design for multi-pattern calibration accordingly. Until recently, the camera calibration planar pattern recognition methods proposed are mainly the recognition of the calibration pattern from images with a single pattern...
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