Structure and Motion from Long Image Sequences

Structure and Motion from Long Image Sequences
Author: Christian Hans Debrunner
Publisher:
Total Pages: 200
Release: 1990
Genre:
ISBN:
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When humans are presented with a sequence of monocular views of a rotating object, they have a vivid perception of the three-dimensional structure of the object. In addition, if an object in the field of view is moving, humans can more easily separate the object from the background than if it were stationary. This thesis presents a computer algorithm which, given a sequence of digital intensity images of moving objects, will separate the images into regions showing distinct objects, and for those objects which are rotating, will calculate the three-dimensional structure and motion. The method involves two major steps: finding and tracking feature points on the objects in the images, and determining the structure and motion of the objects from these feature point trajectories. To find the trajectories, the features of interest in the input images are enhanced, and instead of detecting the features in a single frame, the algorithm then detects the paths of the features as they move over several frames. To determine the structure and motion of the objects, the trajectories must be partitioned into groups corresponding to the different objects, and then for each of these groups, the three-dimensional structure and motion must be found. The structure and motion estimation algorithm requires that the objects are rigid, that the rotational motion is constant, and that the scene containing the objects is orthographically projected on the image plane. This work describes experiments using synthetic data to test the noise sensitivity of the structure and motion estimation algorithm under a variety of conditions. In addition, two real image sequences are used to test the complete algorithm, from tracking the features to finding the structure and motion of each object.

Motion Analysis and Image Sequence Processing

Motion Analysis and Image Sequence Processing
Author: M. Ibrahim Sezan
Publisher: Springer Science & Business Media
Total Pages: 499
Release: 2012-12-06
Genre: Technology & Engineering
ISBN: 1461532361
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An image or video sequence is a series of two-dimensional (2-D) images sequen tially ordered in time. Image sequences can be acquired, for instance, by video, motion picture, X-ray, or acoustic cameras, or they can be synthetically gen erated by sequentially ordering 2-D still images as in computer graphics and animation. The use of image sequences in areas such as entertainment, visual communications, multimedia, education, medicine, surveillance, remote control, and scientific research is constantly growing as the use of television and video systems are becoming more and more common. The boosted interest in digital video for both consumer and professional products, along with the availability of fast processors and memory at reasonable costs, has been a major driving force behind this growth. Before we elaborate on the two major terms that appear in the title of this book, namely motion analysis and image sequence processing, we like to place them in their proper contexts within the range of possible operations that involve image sequences. In this book, we choose to classify these operations into three major categories, namely (i) image sequence processing, (ii) image sequence analysis, and (iii) visualization. The interrelationship among these three categories is pictorially described in Figure 1 below in the form of an "image sequence triangle".

Structure from Motion using the Extended Kalman Filter

Structure from Motion using the Extended Kalman Filter
Author: Javier Civera
Publisher: Springer
Total Pages: 180
Release: 2011-11-09
Genre: Technology & Engineering
ISBN: 3642248349
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The fully automated estimation of the 6 degrees of freedom camera motion and the imaged 3D scenario using as the only input the pictures taken by the camera has been a long term aim in the computer vision community. The associated line of research has been known as Structure from Motion (SfM). An intense research effort during the latest decades has produced spectacular advances; the topic has reached a consistent state of maturity and most of its aspects are well known nowadays. 3D vision has immediate applications in many and diverse fields like robotics, videogames and augmented reality; and technological transfer is starting to be a reality. This book describes one of the first systems for sparse point-based 3D reconstruction and egomotion estimation from an image sequence; able to run in real-time at video frame rate and assuming quite weak prior knowledge about camera calibration, motion or scene. Its chapters unify the current perspectives of the robotics and computer vision communities on the 3D vision topic: As usual in robotics sensing, the explicit estimation and propagation of the uncertainty hold a central role in the sequential video processing and is shown to boost the efficiency and performance of the 3D estimation. On the other hand, some of the most relevant topics discussed in SfM by the computer vision scientists are addressed under this probabilistic filtering scheme; namely projective models, spurious rejection, model selection and self-calibration.

Image Sequence Processing and Dynamic Scene Analysis

Image Sequence Processing and Dynamic Scene Analysis
Author: T. S. Huang
Publisher: Springer Science & Business Media
Total Pages: 759
Release: 2012-12-06
Genre: Computers
ISBN: 3642819354
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This volume contains the proceedings of the NATO Advanced Study Institute on "Image Sequence Processing and Dynamic Scene Analysis" held 21 June - 2 July, 1982 in Hotel Maritim, Braunlage/Harz, Federal Republic of Germany. The organizing eommittee of the institute consists of T.S. Huang (Director), H.G. Musmann (Co Director), H.H. Nagel (Consultant), and C.E. Liedtke and W. Geuen (Local 'arrangement). This Institute was devoted to the rapidly emerging field of image sequence processing and dynamic scene analysis which has man! important applications in cluding target tracking, television bandwidth compression, highway traffic moni toring, and analysis of heart wall motion for medical diagnosis. The lectures and discussions in this Institute fell into three overlapping categories: Motion estimation; pattern recognition and artificial intelligence techniques in dynamic scene analysis; and, applications. 1) Motion estimation - One of the most important problems in image sequence analysis and dynamic scene analysis is displacement and motion estimation. For example, in interframe coding using temporal DPCM, displacement estimation and compensation can improve efficiency significantly. Also, estimated motion parameters can be powerful cues in target segmentation, detection, and classification. In this Institute, a number of recently developed techniques for displacement and motion estimation were discussed.

Guide to Three Dimensional Structure and Motion Factorization

Guide to Three Dimensional Structure and Motion Factorization
Author: Guanghui Wang
Publisher: Springer Science & Business Media
Total Pages: 219
Release: 2010-10-20
Genre: Computers
ISBN: 0857290460
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The problem of structure and motion recovery from image sequences is an important theme in computer vision. Considerable progress has been made in this field during the past two decades, resulting in successful applications in robot navigation, augmented reality, industrial inspection, medical image analysis, and digital entertainment, among other areas. However, many of these methods work only for rigid objects and static scenes. The study of non-rigid structure from motion is not only of academic significance, but also has important practical applications in real-world, nonrigid or dynamic scenarios, such as human facial expressions and moving vehicles. This practical guide/reference provides a comprehensive overview of Euclidean structure and motion recovery, with a specific focus on factorization-based algorithms. The book discusses the latest research in this field, including the extension of the factorization algorithm to recover the structure of non-rigid objects, and presents some new algorithms developed by the authors. Readers require no significant knowledge of computer vision, although some background on projective geometry and matrix computation would be beneficial. Topics and features: presents the first systematic study of structure and motion recovery of both rigid and non-rigid objects from images sequences; discusses in depth the theory, techniques, and applications of rigid and non-rigid factorization methods in three dimensional computer vision; examines numerous factorization algorithms, covering affine, perspective and quasi-perspective projection models; provides appendices describing the mathematical principles behind projective geometry, matrix decomposition, least squares, and nonlinear estimation techniques; includes chapter-ending review questions, and a glossary of terms used in the book. This unique text offers practical guidance in real applications and implementations of 3D modeling systems for practitioners in computer vision and pattern recognition, as well as serving as an invaluable source of new algorithms and methodologies for structure and motion recovery for graduate students and researchers.