A Stochastic Grammar of Images
A Stochastic Grammar of Images

Author: Song-Chun Zhu

Publisher: Now Publishers Inc

Published: 2007

Total Pages: 120

ISBN-13: 1601980604

DOWNLOAD EBOOK

A Stochastic Grammar of Images is the first book to provide a foundational review and perspective of grammatical approaches to computer vision. In its quest for a stochastic and context sensitive grammar of images, it is intended to serve as a unified frame-work of representation, learning, and recognition for a large number of object categories. It starts out by addressing the historic trends in the area and overviewing the main concepts: such as the and-or graph, the parse graph, the dictionary and goes on to learning issues, semantic gaps between symbols and pixels, dataset for learning and algorithms. The proposal grammar presented integrates three prominent representations in the literature: stochastic grammars for composition, Markov (or graphical) models for contexts, and sparse coding with primitives (wavelets). It also combines the structure-based and appearance based methods in the vision literature. At the end of the review, three case studies are presented to illustrate the proposed grammar. A Stochastic Grammar of Images is an important contribution to the literature on structured statistical models in computer vision.

Stochastic Image Grammars for Human Pose Estimation
Stochastic Image Grammars for Human Pose Estimation

Author: Brandon Rothrock

Publisher:

Published: 2013

Total Pages: 141

ISBN-13:

DOWNLOAD EBOOK

Robust human pose estimation is of particular interest to the computer vision community, and can be applied to a broad range of applications such as automated surveillance, human-computer interaction, and human activity recognition. In this dissertation, we present a framework for human pose estimation based on stochastic image grammars. Humans in particular are difficult to model, as their articulated geometry, camera viewpoint, and perspective, can produce a very large number of distinct shapes in images. Furthermore, humans often exhibit highly variant and amorphous part appearances, have self-occlusion, and commonly appear in cluttered environments. Our approach capitalizes on the reconfigurable and modular nature of grammatical models to cope with this variability in both geometry and appearance. We present a human body model as a stochastic context-sensitive AND-OR graph grammar, which represents the body as a hierarchical composition of primitive parts while maintaining the articulated kinematics between parts. Each body instance can be composed from a different set of parts and relations in order to explain the unique shape or appearance of that instance. We present grammar models based on coarse-to-fine phrase-structured grammars as well as dependency grammars, and describe efficient algorithms for learning and inference from both generative and discriminative perspectives. Furthermore, we propose extensions to our model to provide ambiguity reasoning in crowded scenes through the use of composite cluster sampling, and reasoning for self-occlusion and external occlusion of parts. We also present a technique to incorporate image segmentation into the part appearance models to improve localization performance on difficult to detect parts. Finally, we demonstrate the effectiveness of our approach by showing state-of-art performance on several recent public benchmark datasets.

SPATIAL ANALYSIS IN PUBLIC HEALTH DOMAIN: AN NLP APPROACH
SPATIAL ANALYSIS IN PUBLIC HEALTH DOMAIN: AN NLP APPROACH

Author: Pattathal Vijayakumar Arun

Publisher: Infinite Study

Published:

Total Pages: 12

ISBN-13:

DOWNLOAD EBOOK

Remote sensing products are effectively used as a tool for decision making in various fields, especially in medical research and health care analyses. GIS is particularly well suited in this context because of its spatial analysis and display capabilities. The integration of RS techniques in public health has been categorised as continuous and discrete strategies where latter is preferred. We have investigated the integration of these approaches through linguistic interpretation of images. In this paper, we propose a framework for direct natural language interpretation of satellite images using probabilistic grammar rules in conjunction with evolutionary computing techniques. Spectral and spatial information has been dynamically combined using adaptive kernel strategy for effective representation of the contextual knowledge. The developed methodology has been evaluated in different querying contexts and investigations revealed that considerable success has been achieved with the procedure. The methodology has also demonstrated to be effective in intelligent interpolation, automatic interpretation as well as attribute, topology, proximity, and semantic analyses.

Video Analytics for Business Intelligence
Video Analytics for Business Intelligence

Author: Caifeng Shan

Publisher: Springer Science & Business Media

Published: 2012-04-07

Total Pages: 374

ISBN-13: 364228597X

DOWNLOAD EBOOK

Closed Circuit TeleVision (CCTV) cameras have been increasingly deployed pervasively in public spaces including retail centres and shopping malls. Intelligent video analytics aims to automatically analyze content of massive amount of public space video data and has been one of the most active areas of computer vision research in the last two decades. Current focus of video analytics research has been largely on detecting alarm events and abnormal behaviours for public safety and security applications. However, increasingly CCTV installations have also been exploited for gathering and analyzing business intelligence information, in order to enhance marketing and operational efficiency. For example, in retail environments, surveillance cameras can be utilised to collect statistical information about shopping behaviour and preference for marketing (e.g., how many people entered a shop; how many females/males or which age groups of people showed interests to a particular product; how long did they stay in the shop; and what are the frequent paths), and to measure operational efficiency for improving customer experience. Video analytics has the enormous potential for non-security oriented commercial applications. This book presents the latest developments on video analytics for business intelligence applications. It provides both academic and commercial practitioners an understanding of the state-of-the-art and a resource for potential applications and successful practice.

Computer Vision
Computer Vision

Author: Richard Szeliski

Publisher: Springer Science & Business Media

Published: 2010-09-30

Total Pages: 824

ISBN-13: 1848829353

DOWNLOAD EBOOK

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.

Human Behavior Recognition Technologies: Intelligent Applications for Monitoring and Security
Human Behavior Recognition Technologies: Intelligent Applications for Monitoring and Security

Author: Guesgen, Hans W.

Publisher: IGI Global

Published: 2013-03-31

Total Pages: 378

ISBN-13: 1466636831

DOWNLOAD EBOOK

Recently, the ICT field has seen a shift from machine-centered focuses to human and user knowledge-based approaches. However, as priorities shift, questions arise on how to detect and monitor users’ behavior. Human Behavior Recognition Technologies: Intelligent Applications for Monitoring and Security takes an insightful look into the applications and dependability of behavior detection. In addition, this comprehensive publication looks into the social, ethical, and legal implications of these areas. Researchers and practitioners interested in the computational aspects of behavior monitoring as well as the ethical and legal implications will find this reference source beneficial.

Computer Vision Systems
Computer Vision Systems

Author: Mei Chen

Publisher: Springer

Published: 2013-07-11

Total Pages: 381

ISBN-13: 3642394027

DOWNLOAD EBOOK

This book constitutes the refereed proceedings of the 9th International Conference on Computer Vision Systems, ICVS 2013, held in St. Petersburg, Russia, July 16-18, 2013. Proceedings. The 16 revised papers presented with 20 poster papers were carefully reviewed and selected from 94 submissions. The papers are organized in topical sections on image and video capture; visual attention and object detection; self-localization and pose estimation; motion and tracking; 3D reconstruction; features, learning and validation.

Human Centric Visual Analysis with Deep Learning
Human Centric Visual Analysis with Deep Learning

Author: Liang Lin

Publisher: Springer Nature

Published: 2019-11-13

Total Pages: 156

ISBN-13: 9811323879

DOWNLOAD EBOOK

This book introduces the applications of deep learning in various human centric visual analysis tasks, including classical ones like face detection and alignment and some newly rising tasks like fashion clothing parsing. Starting from an overview of current research in human centric visual analysis, the book then presents a tutorial of basic concepts and techniques of deep learning. In addition, the book systematically investigates the main human centric analysis tasks of different levels, ranging from detection and segmentation to parsing and higher-level understanding. At last, it presents the state-of-the-art solutions based on deep learning for every task, as well as providing sufficient references and extensive discussions. Specifically, this book addresses four important research topics, including 1) localizing persons in images, such as face and pedestrian detection; 2) parsing persons in details, such as human pose and clothing parsing, 3) identifying and verifying persons, such as face and human identification, and 4) high-level human centric tasks, such as person attributes and human activity understanding. This book can serve as reading material and reference text for academic professors / students or industrial engineers working in the field of vision surveillance, biometrics, and human-computer interaction, where human centric visual analysis are indispensable in analysing human identity, pose, attributes, and behaviours for further understanding.

Integrated Uncertainty in Knowledge Modelling and Decision Making
Integrated Uncertainty in Knowledge Modelling and Decision Making

Author: Zengchang Qin

Publisher: Springer

Published: 2013-06-20

Total Pages: 229

ISBN-13: 3642395155

DOWNLOAD EBOOK

This book constitutes the refereed proceedings of the International Symposium on Integrated Uncertainty in Knowledge Modeling and Decision Making, IUKM 2013, held in Beijing China, in July 2013. The 19 revised full papers were carefully reviewed and selected from 49 submissions and are presented together with keynote and invited talks. The papers provide a wealth of new ideas and report both theoretical and applied research on integrated uncertainty modeling and management.