04251 -- Imaging Beyond the Pinhole Camera

From 13.06.04 to 18.06.04, the Dagstuhl Seminar 04251 ``Imaging Beyond the Pin-hole Camera. 12th Seminar on Theoretical Foundations of Computer Vision\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

Robustness and Accuracy of Feature-Based Single Image 2-D–3-D Registration Without Correspondences for Image-Guided Intervention

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Disparate View Matching

Matching of disparate views has gained significance in computer vision due to its role in many novel application areas. Being able to match images of the same scene captured during day and night, between a historic and contemporary picture of a scene, and between aerial and ground-level views of a building facade all enable novel applications ranging from loop-closure detection for structure-from-motion and re-photography to geo-localization of a street-level image using reference imagery captured from the air. The goal of this work is to develop novel features and methods that address matching problems where direct appearance-based correspondences are either difficult to obtain or infeasible because of the lack of appearance similarity altogether. To address these problems, we propose methods that span the appearance-geometry spectrum in terms of both the use of these cues as well as the ability of each method to handle variations in appearance and geometry. First, we consider the problem of geo-localization of a query street-level image using a reference database of building facades captured from a bird\u27s eye view. To address this wide-baseline facade matching problem, a novel scale-selective self-similarity feature that avoids direct comparison of appearance between disparate facade images is presented. Next, to address image matching problems with more extreme appearance variation, a novel representation for matchable images expressed in terms of the eigen-functions of the joint graph of the two images is presented. This representation is used to derive features that are persistent across wide variations in appearance. Next, the problem setting of matching between a street-level image and a digital elevation map (DEM) is considered. Given the limited appearance information available in this scenario, the matching approach has to rely more significantly on geometric cues. Therefore, a purely geometric method to establish correspondences between building corners in the DEM and the visible corners in the query image is presented. Finally, to generalize this problem setting we address the problem of establishing correspondences between 3D and 2D point clouds using geometric means alone. A novel framework for incorporating purely geometric constraints into a higher-order graph matching framework is presented with specific formulations for the three-point calibrated absolute camera pose problem (P3P), two-point upright camera pose problem (Up2p) and the three-plus-one relative camera pose problem

Recursive Motion Estimation of Range Image

ABSTRACT In this paper, we present an innovative recursive motion estimation technique that can take advantage of the in-depth resolution (range) to perform an accurate estimation of objects that have undergone 3-D translational and rotational movements. This approach iteratively aims at minimizing the error between the object in the current frame and its compensated object using estimated motion displacement from the previous range measurements. In addition, in order to use the range data on the non-rectangular grid in the Cartesian coordinate, we consider a combination of derivative filters and the transformation between the Cartesian coordinates and the sensor-centered coordinates. For sequences of moving range images we demonstrate the effectiveness of the proposed scheme. , which is more straightforward than the feature-based algorithm. In our approach, which falls in this category, we are mainly concerned with rigid motion where the structure of moving images is based on a single beam laser scanner technology. In this technology a deflection mirror assembly scans a beam over the scene. This type of technique has been widely used for many tactical and industria

Communication Free Robot Swarming

As the military use of unmanned aerial vehicles increases, a growing need for novel strategies to control these systems exists. One such method for controlling many unmanned aerial vehicles simultaneously is the through the use of swarm algorithms. This research explores a swarm robotic algorithm developed by Kadrovach implemented on Pioneer Robots in a real-world environment. An adaptation of his visual sensor is implemented using stereo vision as the primary method of sensing the environment. The swarm members are prohibited from explicitly communicating other than passively through the environment. The resulting implementation produces a communication free swarming algorithm. The algorithm is tested for performance of the visual sensor, performance of the algorithm against stationary targets, and finally, performance against dynamic targets. The results show expected behavior of the swarm model as implemented on the Pioneer robots providing a foundation for future research in swarm algorithms

Correspondence-free stereo vision.

by Yuan, Ding.Thesis submitted in: December 2003.Thesis (M.Phil.)--Chinese University of Hong Kong, 2004.Includes bibliographical references (leaves 69-71).Abstracts in English and Chinese.ABSTRACT --- p.i摘要 --- p.iiiACKNOWLEDGEMENTS --- p.vTABLE OF CONTENTS --- p.viLIST OF FIGURES --- p.viiiLIST OF TABLES --- p.xiiChapter 1 --- INTRODUCTION --- p.1Chapter 2 --- PREVIOUS WORK --- p.5Chapter 2.1 --- Traditional Stereo Vision --- p.5Chapter 2.1.1 --- Epipolar Constraint --- p.7Chapter 2.1.2 --- Some Constraints Based on Properties of Scene Objects --- p.9Chapter 2.1.3 --- Two Classes of Algorithms for Correspondence Establishment --- p.10Chapter 2.2 --- Correspondenceless Stereo Vision Algorithm for Single Planar Surface Recovery under Parallel-axis Stereo Geometry --- p.13Chapter 3 --- CORRESPONDENCE-FREE STEREO VISION UNDER GENERAL STEREO SETUP --- p.19Chapter 3.1 --- Correspondence-free Stereo Vision Algorithm for Single Planar Surface Recovery under General Stereo Geometry --- p.20Chapter 3.1.1 --- Algorithm in Its Basic Form --- p.21Chapter 3.1.2 --- Algorithm Combined with Epipolar Constraint --- p.25Chapter 3.1.3 --- Algorithm Combined with SVD And Robust Estimation --- p.36Chapter 3.2 --- Correspondence-free Stereo Vision Algorithm for Multiple Planar Surface Recovery --- p.45Chapter 3.2.1 --- Plane Hypothesis --- p.46Chapter 3.2.2 --- Plane Confirmation And 3D Reconstruction --- p.48Chapter 3.2.3 --- Experimental Results --- p.50Chapter 3.3 --- Experimental Results on Correspondence-free Vs. Correspondence Based Methods --- p.60Chapter 4 --- CONCLUSION AND FUTURE WORK --- p.65APPENDIX --- p.67BIBLIOGRAPHY --- p.6

3-D structure recovery using unified optical flow field approach

Recovery of the 3-D structure that is characterized by an Nth order factorable and/or non-factorable polynomial equation is studied in this thesis. Analytical tools have been employed to analyze and solve the problem. The solution is based on the direct method, which is derived from the unified optical flow field, which, in turn, is an extension of optical flow to spatial image sequences. Least squares formulation has been employed for optimum estimation. The method used does not require the establishment of point to point correspondence, nor the estimation of the optical flow, as an intermediate step. The theoretical results are tested using some synthetic images of various structures including cone, parabola and the combination of a cone and a planar surface. Satisfactory results are obtained, thus demonstrating the validity of the newly developed technique for the recovery of a variety of surfaces [14]

Statistical shape modeling of the left ventricle: myocardial infarct classification challenge

Statistical shape modeling is a powerful tool for visualizing and quantifying geometric and functional patterns of the heart. After myocardial infarction (MI), the left ventricle typically remodels in response to physiological challenges. Several methods have been proposed in the literature to describe statistical shape changes. Which method best characterizes left ventricular remodeling after MI is an open research question. A better descriptor of remodeling is expected to provide a more accurate evaluation of disease status in MI patients. We therefore designed a challenge to test shape characterization in MI given a set of three-dimensional left ventricular surface points. The training set comprised 100 MI patients, and 100 asymptomatic volunteers (AV). The challenge was initiated in 2015 at the Statistical Atlases and Computational Models of the Heart workshop, in conjunction with the MICCAI conference. The training set with labels was provided to participants, who were asked to submit the likelihood of MI from a different (validation) set of 200 cases (100 AV and 100 MI). Sensitivity, specificity, accuracy and area under the receiver operating characteristic curve were used as the outcome measures. The goals of this challenge were to (1) establish a common dataset for evaluating statistical shape modeling algorithms in MI, and (2) test whether statistical shape modeling provides additional information characterizing MI patients over standard clinical measures. Eleven groups with a wide variety of classification and feature extraction approaches participated in this challenge. All methods achieved excellent classification results with accuracy ranges from 0.83 to 0.98. The areas under the receiver operating characteristic curves were all above 0.90. Four methods showed significantly higher performance than standard clinical measures. The dataset and software for evaluation are available from the Cardiac Atlas Project website1