Download or read book Deformable and Articulated 3D Reconstruction from Monocular Video Sequences written by Marco Paladini and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis addresses the problem of deformable and articulated structure from motion from monocular uncalibrated video sequences. Structure from motion is defined as the problem of recovering information about the 3D structure of scenes imaged by a camera in a video sequence. Our study aims at the challenging problem of non-rigid shapes (e.g. a beating heart or a smiling face). Non-rigid structures appear constantly in our everyday life, think of a bicep curling, a torso twisting or a smiling face. Our research seeks a general method to perform 3D shape recovery purely from data, without having to rely on a pre-computed model or training data. Open problems in the field are the difficulty of the non-linear estimation, the lack of a real-time system, large amounts of missing data in real-world video sequences, measurement noise and strong deformations. Solving these problems would take us far beyond the current state of the art in non-rigid structure from motion. This dissertation presents our contributions in the field of non-rigid structure from motion, detailing a novel algorithm that enforces the exact metric structure of the problem at each step of the minimisation by projecting the motion matrices onto the correct deformable or articulated metric motion manifolds respectively. An important advantage of this new algorithm is its ability to handle missing data which becomes crucial when dealing with real video sequences. We present a generic bilinear estimation framework, which improves convergence and makes use of the manifold constraints. Finally, we demonstrate a sequential, frame-by-frame estimation algorithm, which provides a 3D model and camera parameters for each video frame, while simultaneously building a model of object deformations.
Download or read book Deformable Surface 3D Reconstruction from Monocular Images written by Mathieu Salzmann and published by Morgan & Claypool Publishers. This book was released on 2011 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt: 7. Future directions -- Bibliography -- Authors' biographies.
Download or read book Articulated Motion and Deformable Objects written by Francisco José Perales and published by Springer. This book was released on 2016-07-06 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 9th International Conference on Articulated Motion and Deformable Objects, AMDO 2016, held in Palma de Mallorca, Spain, in July 2016.The 20 papers presented were carefully reviewed and selected from 34 submissions. The conference dealt with the following topics: advanced computer graphics and immersive videogames; human modeling and animation; human motion analysis and tracking; 3D human reconstruction and recognition; multimodal user interaction and applications; ubiquitous and social computing; design tools; input technology; programming user interfaces; 3D medical deformable models and visualization; deep learning methods for computer vision and graphics; multibiometric.
Download or read book Articulated Motion and Deformable Objects written by Francisco J. Perales and published by Springer. This book was released on 2004-08-20 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: The AMDO 2004 workshop took place at the Universitat de les Illes Balears (UIB) on 22-24 September, 2004, institutionally sponsored by the International Association for Pattern Recognition (IAPR), the MCYT (Comision Interm- isterial de Ciencia y Tecnologia, Spanish Government), the AERFAI (Spanish Association for Pattern Recognition and Image Analysis), the EG (Eurogra- ics Association) and the Mathematics and Computer Science Department of the UIB. Also important commercial sponsors collaborated with practical dem- strations; the main contributors were: Barco Electronics Systems (Title Sp- sor), VICOM Tech, ANDROME Iberica, CESA and TAGrv. The subject of the workshop was ongoing research in articulated motion on a sequence of images and sophisticated models for deformable objects. The goals of these areas are to understand and interpret the motion of complex objects that can be found in sequences of images in the real world. The main topics considered priorities are: deformable models, motion analysis, articulated models and animation, visualization of deformable models, 3D recovery from motion, single or multiple human motion analysis and synthesis, applications of deformable models and motion analysis, face tracking, recovery and recognition models, and virtual and augmented reality systems.
Download or read book Robust Methods for Dense Monocular Non Rigid 3D Reconstruction and Alignment of Point Clouds written by Vladislav Golyanik and published by Springer Nature. This book was released on 2020-06-04 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Vladislav Golyanik proposes several new methods for dense non-rigid structure from motion (NRSfM) as well as alignment of point clouds. The introduced methods improve the state of the art in various aspects, i.e. in the ability to handle inaccurate point tracks and 3D data with contaminations. NRSfM with shape priors obtained on-the-fly from several unoccluded frames of the sequence and the new gravitational class of methods for point set alignment represent the primary contributions of this book. About the Author: Vladislav Golyanik is currently a postdoctoral researcher at the Max Planck Institute for Informatics in Saarbrücken, Germany. The current focus of his research lies on 3D reconstruction and analysis of general deformable scenes, 3D reconstruction of human body and matching problems on point sets and graphs. He is interested in machine learning (both supervised and unsupervised), physics-based methods as well as new hardware and sensors for computer vision and graphics (e.g., quantum computers and event cameras).
Download or read book Articulated Motion and Deformable Objects written by Francisco Jose Perales Lopez and published by Springer. This book was released on 2012-06-26 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 7th International Conference on Articulated Motion and Deformable Objects, AMDO 2012, held in Port d'Andratx, Mallorca, Spain, in July 2012. The 27 papers presented were carefully reviewed and selected from 44 submissions. The volume also contains one full paper length invited talk. The conference dealt with the following topics: advanced computer graphics (human modeling and animation); human motion (analysis, tracking, 3D reconstruction and recognition); multimodal user interaction and applications; and affective interfaces (recognition and interpretation of emotions, ECAs -- embodied conversational agents in HCI).
Download or read book Articulated Motion and Deformable Objects written by and published by . This book was released on 2004 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book State of the Art in Dense Monocular Non rigid 3D Reconstruction written by and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: 3D reconstruction of deformable (or non-rigid) scenes from a set of monocular 2D image observations is a long-standing and actively researched area of computer vision and graphics. It is an ill-posed inverse problem, since--without additional prior assumptions--it permits infinitely many solutions leading to accurate projection to the input 2D images. Non-rigid reconstruction is a foundational building block for downstream applications like robotics, AR/VR, or visual content creation. The key advantage of using monocular cameras is their omnipresence and availability to the end users as well as their ease of use compared to more sophisticated camera set-ups such as stereo or multi-view systems. This survey focuses on state-of-the-art methods for dense non-rigid 3D reconstruction of various deformable objects and composite scenes from monocular videos or sets of monocular views. It reviews the fundamentals of 3D reconstruction and deformation modeling from 2D image observations. We then start from general methods--that handle arbitrary scenes and make only a few prior assumptions--and proceed towards techniques making stronger assumptions about the observed objects and types of deformations (e.g. human faces, bodies, hands, and animals). A significant part of this STAR is also devoted to classification and a high-level comparison of the methods, as well as an overview of the datasets for training and evaluation of the discussed techniques. We conclude by discussing open challenges in the field and the social aspects associated with the usage of the reviewed methods
Download or read book Variation Based Dense 3D Reconstruction written by Sven Painer and published by Springer. This book was released on 2016-03-08 with total page 87 pages. Available in PDF, EPUB and Kindle. Book excerpt: In his master thesis, Sven Painer develops, implements, and evaluates a method to reconstruct the liver surface from monocular mini-laparoscopic sequences. The principal focus of his research is to create a basis for helping clinicians to write reports with quantitative descriptions of the liver surface. A Structure from Motion approach is performed to do a sparse reconstruction of the liver surface and subsequently this information is used in a variation based dense 3D reconstruction. The algorithms are formulated in a causal way, enabling the implementation to be run in real-time on an adequate hardware platform. The results show a significant performance increase and pave the way to give clinicians a feedback during video capturing to improve the quality of the reconstruction in the near future.
Download or read book Statistical Analysis of 3D Modeling from Monocular Video Streams written by Amit K. Roy-Chowdhury and published by . This book was released on 2002 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: 3D scene modeling from a video sequence is considered to be one of the most important problems in computer vision. Its successful solution has numerous possibilities in applications like multimedia communications, surveillance, virtual reality, automatic navigation, medical prognosis, etc. One of the most powerful techniques for solving this problem is known as structure from motion (SfM). Briefy, the SfM problem is about recovering the absolute or relative depth of static and moving objects using video acquired from single or multiple video cameras. The most challenging problem is when only a monocular video is present and we require a dense estimate of the depth. Successful solution of this problem requires a detailed understanding of the geometry of the 3D world and its 2D projections on the image planes. However, the motion between adjacent frames of a video sequence is usually very small, thus introducing large errors in its estimation. Hence, in order to obtain a satisfactory solution, it is important to understand the statistics of these errors and their in teraction with the geometry of the problem. The overall aim of this thesis is to show how to combine the statistics describing the quality of the input video data with an understanding of the geometry, in order to obtain an accurate 3D scene reconstruction from a video sequence using the optical flow model. In our work, we pose the 3D reconstruction problem in an estimation-theoretic framew ork. We adopt the optical flow paradigm for modeling the motion between the frames of the video sequence. We show how the statistics of the errors in the input motion estimates are propagated through the 3D reconstruction algorithm and affect the quality of the output. We present a new result: that the 3D estimate is always statistically biased, and the magnitude of this bias is signifficant. In order to demonstrate our analysis in a practical application, we consider the problem of reconstructing a 3D model of a human face from video. An algorithm is proposed that obtains a robust 3D model by fusing two-frame estimates using stochastic approximation theory and then combines it with a generic face model in a Markov chain Monte Carlo optimization procedure. We address the question of how to automatically evaluate the quality of a 3D reconstruction from a video sequence, and presen a criterion using concepts from information theory . Finally, we propose a probabilistic registration algorithm that extends the results of our work to create holistic 3D models from multiple video streams.
Download or read book Computer Vision ECCV 2016 written by Bastian Leibe and published by Springer. This book was released on 2016-09-15 with total page 893 pages. Available in PDF, EPUB and Kindle. Book excerpt: The eight-volume set comprising LNCS volumes 9905-9912 constitutes the refereed proceedings of the 14th European Conference on Computer Vision, ECCV 2016, held in Amsterdam, The Netherlands, in October 2016. The 415 revised papers presented were carefully reviewed and selected from 1480 submissions. The papers cover all aspects of computer vision and pattern recognition such as 3D computer vision; computational photography, sensing and display; face and gesture; low-level vision and image processing; motion and tracking; optimization methods; physics-based vision, photometry and shape-from-X; recognition: detection, categorization, indexing, matching; segmentation, grouping and shape representation; statistical methods and learning; video: events, activities and surveillance; applications. They are organized in topical sections on detection, recognition and retrieval; scene understanding; optimization; image and video processing; learning; action, activity and tracking; 3D; and 9 poster sessions.
Download or read book Resolving Ambiguities in Monocular 3D Reconstruction of Deformable Surfaces written by Aydin Varol and published by . This book was released on 2012 with total page 115 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Computer Vision ECCV 2014 written by David Fleet and published by Springer. This book was released on 2014-09-22 with total page 632 pages. Available in PDF, EPUB and Kindle. Book excerpt: The seven-volume set comprising LNCS volumes 8689-8695 constitutes the refereed proceedings of the 13th European Conference on Computer Vision, ECCV 2014, held in Zurich, Switzerland, in September 2014. The 363 revised papers presented were carefully reviewed and selected from 1444 submissions. The papers are organized in topical sections on tracking and activity recognition; recognition; learning and inference; structure from motion and feature matching; computational photography and low-level vision; vision; segmentation and saliency; context and 3D scenes; motion and 3D scene analysis; and poster sessions.
Download or read book Human Motion written by Bodo Rosenhahn and published by Springer Science & Business Media. This book was released on 2008 with total page 628 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book which informs about recent progress in biomechanics, computer vision and computer graphics – all in one volume. Researchers from these areas have contributed to this book to promote the establishment of human motion research as a multi-facetted discipline and to improve the exchange of ideas and concepts between these three areas. The book combines carefully written reviews with detailed reports on recent progress in research.
Download or read book Multi view Approaches to Tracking 3D Reconstruction and Object Class Detection written by Saad M. Khan and published by . This book was released on 2008 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multi-camera systems are becoming ubiquitous and have found application in a variety of domains including surveillance, immersive visualization, sports entertainment and movie special effects amongst others. From a computer vision perspective, the challenging task is how to most efficiently fuse information from multiple views in the absence of detailed calibration information and a minimum of human intervention. This thesis presents a new approach to fuse foreground likelihood information from multiple views onto a reference view without explicit processing in 3D space, thereby circumventing the need for complete calibration. Our approach uses a homographic occupancy constraint (HOC), which states that if a foreground pixel has a piercing point that is occupied by foreground object, then the pixel warps to foreground regions in every view under homographies induced by the reference plane, in effect using cameras as occupancy detectors. Using the HOC we are able to resolve occlusions and robustly determine ground plane localizations of the people in the scene. To find tracks we obtain ground localizations over a window of frames and stack them creating a space time volume. Regions belonging to the same person form contiguous spatio-temporal tracks that are clustered using a graph cuts segmentation approach. Second, we demonstrate that the HOC is equivalent to performing visual hull intersection in the image-plane, resulting in a cross-sectional slice of the object. The process is extended to multiple planes parallel to the reference plane in the framework of plane to plane homologies. Slices from multiple planes are accumulated and the 3D structure of the object is segmented out. Unlike other visual hull based approaches that use 3D constructs like visual cones, voxels or polygonal meshes requiring calibrated views, ours is purely-image based and uses only 2D constructs i.e. planar homographies between views. This feature also renders it conducive to graphics hardware acceleration. The current GPU implementation of our approach is capable of fusing 60 views (480x720 pixels) at the rate of 50 slices/second. We then present an extension of this approach to reconstructing non-rigid articulated objects from monocular video sequences. The basic premise is that due to motion of the object, scene occupancies are blurred out with non-occupancies in a manner analogous to motion blurred imagery. Using our HOC and a novel construct: the temporal occupancy point (TOP), we are able to fuse multiple views of non-rigid objects obtained from a monocular video sequence. The result is a set of blurred scene occupancy images in the corresponding views, where the values at each pixel correspond to the fraction of total time duration that the pixel observed an occupied scene location. We then use a motion de-blurring approach to de-blur the occupancy images and obtain the 3D structure of the non-rigid object. In the final part of this thesis, we present an object class detection method employing 3D models of rigid objects constructed using the above 3D reconstruction approach. Instead of using a complicated mechanism for relating multiple 2D training views, our approach establishes spatial connections between these views by mapping them directly to the surface of a 3D model. To generalize the model for object class detection, features from supplemental views (obtained from Google Image search) are also considered. Given a 2D test image, correspondences between the 3D feature model and the testing view are identified by matching the detected features. Based on the 3D locations of the corresponding features, several hypotheses of viewing planes can be made. The one with the highest confidence is then used to detect the object using feature location matching. Performance of the proposed method has been evaluated by using the PASCAL VOC challenge dataset and promising results are demonstrated.
Download or read book Contributions to Monocular Deformable 3D Reconstruction written by Mathias Gallardo and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Monocular deformable 3D reconstruction is the general problem of recovering the 3D shape of a deformable object from monocular 2D images. Several scenarios have emerged: the Shape-from-Template (SfT) and the Non-Rigid Structure-from-Motion (NRSfM) are two approaches intensively studied for their practicability. The former uses a single image depicting the deforming object and a template (a textured 3D shape of this object in a reference pose). The latter does not use a template, but uses several images and recovers the 3D shape in each image. Both approaches rely on the motion of correspondences between the images and deformation priors, which restrict their use to well-textured surfaces which deform smoothly. This thesis advances the state-of-the-art in SfT and NRSfM in two main directions. The first direction is to study SfT for the case of 1D templates (i.e. curved, thin structures such as ropes and cables). The second direction is to develop algorithms in SfT and NRSfM that exploit multiple visual cues and can solve complex, real-world cases which were previously unsolved. We focus on isometric deformations and reconstruct the outer part of the object. The technical and scientific contributions of this thesis are divided into four parts. The first part of this thesis studies the case of a curvilinear template embedded in 2D or 3D space, referred to Curve SfT. We propose a thorough theoretical analysis and practical solutions for Curve SfT. Despite its apparent simplicity, Curve SfT appears to be a complex problem: it cannot be solved locally using exact non-holonomic partial differential equation and is only solvable up to a finite number of ambiguous solutions. A major technical contribution is a computational solution based on our theory, which generates all the ambiguous solutions.The second part of this thesis deals with a limitation of SfT methods: reconstructing creases. This is due to the sparsity of the motion constraint and regularization. We propose two contributions which rely on a non-convex energy minimization framework. First, we complement the motion constraint with a robust boundary contour constraint. Second, we implicitly model creases with a dense mesh-based surface representation and an associated robust smoothing constraint, which deactivates curvature smoothing automatically where needed, without knowing a priori the crease location. The third part of this thesis is dedicated to another limitation of SfT: reconstructing poorly-textured surfaces. This is due to correspondences which cannot be obtained so easily on poorly-textured surfaces (either sparse or dense). As shading reveals details on poorly-textured surfaces, we propose to combine shading and SfT. We have two contributions. The first is a cascaded initialization which estimates sequentially the surface's deformation, the scene illumination, the camera response and then the surface albedos from deformed monocular images. The second is to integrate shading to our previous energy minimization framework for simultaneously refining deformation and photometric parameters.The last part of this thesis relaxes the knowledge of the template and addresses two limitations of NRSfM: reconstructing poorly-textured surfaces with creases. Our major contribution is an extension of the second framework to recover jointly the 3D shapes of all input images and the surface albedos without any template.
Download or read book Computer Vision ECCV 2014 written by David Fleet and published by Springer. This book was released on 2014-08-14 with total page 656 pages. Available in PDF, EPUB and Kindle. Book excerpt: The seven-volume set comprising LNCS volumes 8689-8695 constitutes the refereed proceedings of the 13th European Conference on Computer Vision, ECCV 2014, held in Zurich, Switzerland, in September 2014. The 363 revised papers presented were carefully reviewed and selected from 1444 submissions. The papers are organized in topical sections on tracking and activity recognition; recognition; learning and inference; structure from motion and feature matching; computational photography and low-level vision; vision; segmentation and saliency; context and 3D scenes; motion and 3D scene analysis; and poster sessions.
