Humans perceive the three-dimensional structure of the world with apparent ease. However, despite all of the recent advances in computer vision research, the dream of having a computer interpret an image at the same level as a two-year old remains elusive. Why is computer vision such a challenging problem and what is the current state of the art? Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos. More than just a source of recipes, this exceptionally authoritative and comprehensive textbook/reference also takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene. These problems are also analyzed using statistical models and solved using rigorous engineering techniques Topics and features: structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses; presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects; provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, and Bayesian estimation theory; suggests additional reading at the end of each chapter, including the latest research in each sub-field, in addition to a full Bibliography at the end of the book; supplies supplementary course material for students at the associated website, http://szeliski.org/Book/. Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.

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Computer Vision: Algorithms and Applications

http://cvssp-data.eps.surrey.ac.uk/Personal/AdrianHilton/Publications_files/survey_techrep.pdf

A survey of advances in vision-based human motion capture and analysis

MEDICAL LITERATURE has been deluged during the past few years with books and papers on penicillin; but a book which has been produced under the general editorship of Sir Alexander Fleming himself represents a complete and authoritative summary of penicillin therapy as it stands today.' The book contains a series of independent contributions by \"experienced and eminent men who have worked with penicillin in Great Britain\". Their opinions and practical methods differ slightly, and there is some overlapping; but these are not disadvantageous, comparison and contrast lending interest to the reading. In the first or general section of the book Fleming contributes two chapters, one on the history and development of penicillin, introducing some interesting sidelights in the romance of discovery, the other on the bacteriological control of penicillin therapy. In both chapters the information is set out in meticulous detail and with a clarity and simplicity which can be enjoyed by all readers. Fleming also gives the right perspective to the place of penicillin amongst the antibiotics and lays down the principles of treatment. Both chapters are well illustrated and are the most outstanding in the book. Included in this first section also are chapters on the chemistry and manufacture of penicillin and its pharmacy, pharmacology and methods of administration. The second section of the book is entirely clinical, giving each author's view on the use of penicillin therapy in a disease or an infection of some particular region of the body. The entire range of peniCillin-sensitive conditions is considered in twenty authoritative and clearly written chapters; these contain many references and illustrations. Dental and veterinary diseases are also given fairly full consideration. The final section is a condensed resume of much of the preceding chapters and is written for. the general practttioner. This chapter is superttuous: it does not contain enough detall to be of much practical value. The book as a Whole, however, will undoubtedly be considered a classical contribution to medical literature and is strongly recommended, not only because of the general interest of its topic, but as a reference book on penicillin therapy of hitherto unequalled excellence. The typography, although conforming to war economy standards, is clear and the paper is good. There is an excellent list of references and the index is satisfactory.

Gray's Anatomy

This article develops methods for determining visually appealing motion transitions using linear blending. Motion transitions are segues between two sequences of animation, and are important components for generating compelling animation streams in virtual environments and computer games. Methods involving linear blending are studied because of their efficiency, computational speed, and widespread use. Two methods of transition specification are detailed, center-aligned and start-end transitions. First, we compute a set of optimal weights for an underlying cost metric used to determine the transition points. We then evaluate the optimally weighted cost metric for generalizability, appeal, and robustness through a cross-validation and user study. Next, we develop methods for computing visually appealing blend lengths for two broad categories of motion. We empirically evaluate these results through user studies. Finally, we assess the importance of these techniques by determining the minimum sensitivity of viewers to transition durations, the just noticeable difference, for both center-aligned and start-end specifications.

Synthesis and evaluation of linear motion transitions

In this paper, we propose a new aerial video dataset and benchmark for low altitude UAV target tracking, as well as, a photo-realistic UAV simulator that can be coupled with tracking methods. Our benchmark provides the first evaluation of many state-of-the-art and popular trackers on 123 new and fully annotated HD video sequences captured from a low-altitude aerial perspective. Among the compared trackers, we determine which ones are the most suitable for UAV tracking both in terms of tracking accuracy and run-time. The simulator can be used to evaluate tracking algorithms in real-time scenarios before they are deployed on a UAV “in the field”, as well as, generate synthetic but photo-realistic tracking datasets with automatic ground truth annotations to easily extend existing real-world datasets. Both the benchmark and simulator are made publicly available to the vision community on our website to further research in the area of object tracking from UAVs. (https://ivul.kaust.edu.sa/Pages/pub-benchmark-simulator-uav.aspx.).

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A Benchmark and Simulator for UAV Tracking

Real-time control of three-dimensional avatars is an important problem in the context of computer games and virtual environments. Avatar animation and control is difficult, however, because a large repertoire of avatar behaviors must be made available, and the user must be able to select from this set of behaviors, possibly with a low-dimensional input device. One appealing approach to obtaining a rich set of avatar behaviors is to collect an extended, unlabeled sequence of motion data appropriate to the application. In this paper, we show that such a motion database can be preprocessed for flexibility in behavior and efficient search and exploited for real-time avatar control. Flexibility is created by identifying plausible transitions between motion segments, and efficient search through the resulting graph structure is obtained through clustering. Three interface techniques are demonstrated for controlling avatar motion using this data structure: the user selects from a set of available choices, sketches a path through an environment, or acts out a desired motion in front of a video camera. We demonstrate the flexibility of the approach through four different applications and compare the avatar motion to directly recorded human motion.

Interactive control of avatars animated with human motion data

This paper presents a technique for adapting existing motion of a human-like character to have the desired features that are specified by a set of constraints This problem can be typically formulated as a spacetime constraint problem Our approach combines a hierarchical curve fitting technique with a new inverse kinematics solver Using the kinematics solver, we can adjust the configuration of an articulated figure to meet the constraints in each frame Through the fitting technique, the motion displacement of every joint at each constrained frame is interpolated and thus smoothly propagated to frames We are able to adaptively add motion details to satisfy the constraints within a specified tolerance by adopting a multilevel Bspline representation which also provides a speedup for the interpolation The performance of our system is further enhanced by the new inverse kinematics solver We present a closed-form solution to compute the joint angles of a limb linkage This analytical method greatly reduces the burden of a numerical optimization to find the solutions for full degrees of freedom of a human-like articulated figure We demonstrate that the technique can be used for retargetting a motion to compensate for geometric variations caused by both characters and environments Furthermore, we can also use this technique for directly manipulating a motion clip through a graphical interface CR Categories: I37 [Computer Graphics]: Threedimensional Graphics—Animation; G12 [Numerical Analysis]: Approximation—Spline and piecewise polynomial approximation

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A hierarchical approach to interactive motion editing for human-like figures

Crowd simulation techniques have frequently been used to animate a large group of virtual humans in computer graphics applications. We present a data-driven method of simulating a crowd of virtual humans that exhibit behaviors imitating real human crowds. To do so, we record the motion of a human crowd from an aerial view using a camcorder, extract the two-dimensional moving trajectories of each individual in the crowd, and then learn an agent model from observed trajectories. The agent model decides each agent's actions based on features of the environment and the motion of nearby agents in the crowd. Once the agent model is learned, we can simulate a virtual crowd that behaves similarly to the real crowd in the video. The versatility and flexibility of our approach is demonstrated through examples in which various characteristics of group behaviors are captured and reproduced in simulated crowds.

Group behavior from video: a data-driven approach to crowd simulation

Computer puppetry maps the movements of a performer to an animated character in real-time. In this article, we provide a comprehensive solution to the problem of transferring the observations of the motion capture sensors to an animated character whose size and proportion may be different from the performer's. Our goal is to map as many of the important aspects of the motion to the target character as possible, while meeting the online, real-time demands of computer puppetry. We adopt a Kalman filter scheme that addresses motion capture noise issues in this setting. We provide the notion of dynamic importance of an end-effector that allows us to determine what aspects of the performance must be kept in the resulting motion. We introduce a novel inverse kinematics solver that realizes these important aspects within tight real-time constraints. Our approach is demonstrated by its application to broadcast television performances.

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Computer puppetry: An importance-based approach

Physically based simulation of human motions is an important issue in the context of computer animation, robotics and biomechanics. We present a new technique for allowing our physically-simulated planar biped characters to imitate human behaviors. Our contribution is twofold. We developed an optimization method that transforms any (either motion-captured or kinematically synthesized) biped motion into a physically-feasible, balance-maintaining simulated motion. Our optimization method allows us to collect a rich set of training data that contains stylistic, personality-rich human behaviors. Our controller learning algorithm facilitates the creation and composition of robust dynamic controllers that are learned from training data. We demonstrate a planar articulated character that is dynamically simulated in real time, equipped with an integrated repertoire of motor skills, and controlled interactively to perform desired motions.

/pdf/simulating-biped-behaviors-from-human-motion-data-4ygkfpbmkq.pdf

Jehee Lee

Papers

Interactive control of avatars animated with human motion data

A hierarchical approach to interactive motion editing for human-like figures

Group behavior from video: a data-driven approach to crowd simulation

Computer puppetry: An importance-based approach

Simulating biped behaviors from human motion data