Semantic Analysis of Image Sequences Using Computer Vision Methods

Semantic Analysis of Image Sequences Using Computer Vision Methods PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 111

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Book Description
Observing, learning, and imitating human skills are intriguing topics in cognitive robotics. The main problem in the imitation learning paradigm is the policy development. Policy can be defined as a mapping from an agent's current world state to actions. Thus, understanding and performing an observed human skill for a cognitive agent depends heavily upon the learned policy. So far, naive policies that use object and hand models with trajectory information have commonly been developed to encode and imitate various types of human manipulations. These approaches, on the one hand, can not be ge...

Semantic Analysis of Image Sequences Using Computer Vision Methods

Semantic Analysis of Image Sequences Using Computer Vision Methods PDF Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 111

Get Book Here

Book Description
Observing, learning, and imitating human skills are intriguing topics in cognitive robotics. The main problem in the imitation learning paradigm is the policy development. Policy can be defined as a mapping from an agent's current world state to actions. Thus, understanding and performing an observed human skill for a cognitive agent depends heavily upon the learned policy. So far, naive policies that use object and hand models with trajectory information have commonly been developed to encode and imitate various types of human manipulations. These approaches, on the one hand, can not be ge...

Semantic Analysis and Understanding of Human Behavior in Video Streaming

Semantic Analysis and Understanding of Human Behavior in Video Streaming PDF Author: Alberto Amato
Publisher: Springer Science & Business Media
ISBN: 1461454867
Category : Computers
Languages : en
Pages : 111

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Book Description
Semantic Analysis and Understanding of Human Behaviour in Video Streaming investigates the semantic analysis of the human behaviour captured by video streaming, and introduces both theoretical and technological points of view. Video analysis based on the semantic content is in fact still an open issue for the computer vision research community, especially when real-time analysis of complex scenes is concerned. This book explores an innovative, original approach to human behaviour analysis and understanding by using the syntactical symbolic analysis of images and video streaming described by means of strings of symbols. A symbol is associated to each area of the analyzed scene. When a moving object enters an area, the corresponding symbol is appended to the string describing the motion. This approach allows for characterizing the motion of a moving object with a word composed by symbols. By studying and classifying these words we can categorize and understand the various behaviours. The main advantage of this approach lies in the simplicity of the scene and motion descriptions so that the behaviour analysis will have limited computational complexity due to the intrinsic nature both of the representations and the related operations used to manipulate them. Besides, the structure of the representations is well suited for possible parallel processing, thus allowing for speeding up the analysis when appropriate hardware architectures are used. A new methodology for design systems for hierarchical high semantic level analysis of video streaming in narrow domains is also proposed. Guidelines to design your own system are provided in this book. Designed for practitioners, computer scientists and engineers working within the fields of human computer interaction, surveillance, image processing and computer vision, this book can also be used as secondary text book for advanced-level students in computer science and engineering.

Semantic Networks for Understanding Scenes

Semantic Networks for Understanding Scenes PDF Author: Gerhard Sagerer
Publisher: Springer Science & Business Media
ISBN: 1489919139
Category : Computers
Languages : en
Pages : 507

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Book Description
Figure 1.1. An outdoor scene "A bus is passing three cars which are parking between trees at the side of the road. Houses having two storeys are lined up at the street. 3 4 Introduction Figure 1.2. An assembly scene There seems to be a small open place between the group of houses in the foreground and the store in the background". In such or a similar way the content of the natural scene shown above can be described. It is quite easy to give such a short description. The problem is somewhat more complex for the second image. First of all, it can be stated that the image does not show an everyday scene. It appears as a kind of man made surrounding. But everyone can accept the following statements about this image: 1. The image shows a snapshot of an assembly line. 2. The robot in front is screwing. 3. There is no person in the working area of the robots. 4. All objects on the conveyor belt are worked on by robots. There are no free objects on the belt.

Bridging the Semantic Gap in Image and Video Analysis

Bridging the Semantic Gap in Image and Video Analysis PDF Author: Halina Kwaśnicka
Publisher: Springer
ISBN: 3319738917
Category : Technology & Engineering
Languages : en
Pages : 171

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Book Description
This book presents cutting-edge research on various ways to bridge the semantic gap in image and video analysis. The respective chapters address different stages of image processing, revealing that the first step is a future extraction, the second is a segmentation process, the third is object recognition, and the fourth and last involve the semantic interpretation of the image. The semantic gap is a challenging area of research, and describes the difference between low-level features extracted from the image and the high-level semantic meanings that people can derive from the image. The result greatly depends on lower level vision techniques, such as feature selection, segmentation, object recognition, and so on. The use of deep models has freed humans from manually selecting and extracting the set of features. Deep learning does this automatically, developing more abstract features at the successive levels. The book offers a valuable resource for researchers, practitioners, students and professors in Computer Engineering, Computer Science and related fields whose work involves images, video analysis, image interpretation and so on.

Principles of Visual Information Retrieval

Principles of Visual Information Retrieval PDF Author: Michael S. Lew
Publisher: Springer Science & Business Media
ISBN: 1447137027
Category : Computers
Languages : en
Pages : 366

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Book Description
This text introduces the basic concepts and techniques in VIR. In doing so, it develops a foundation for further research and study. Divided into two parts, the first part describes the fundamental principles. A chapter is devoted to each of the main features of VIR, such as colour, texture and shape-based search. There is coverage of search techniques for time-based image sequences or videos, and an overview of how to combine all the basic features described and integrate them into the search process. The second part looks at advanced topics such as multimedia query. This book is essential reading for researchers in VIR, and final-year undergraduate and postgraduate students on courses such as Multimedia Information Retrieval, Multimedia Databases, and others.

Image Processing, Analysis and Machine Vision

Image Processing, Analysis and Machine Vision PDF Author: Milan Sonka
Publisher: Springer
ISBN: 148993216X
Category : Computers
Languages : en
Pages : 579

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Book Description
Image Processing, Analysis and Machine Vision represent an exciting part of modern cognitive and computer science. Following an explosion of inter est during the Seventies, the Eighties were characterized by the maturing of the field and the significant growth of active applications; Remote Sensing, Technical Diagnostics, Autonomous Vehicle Guidance and Medical Imaging are the most rapidly developing areas. This progress can be seen in an in creasing number of software and hardware products on the market as well as in a number of digital image processing and machine vision courses offered at universities world-wide. There are many texts available in the areas we cover - most (indeed, all of which we know) are referenced somewhere in this book. The subject suffers, however, from a shortage of texts at the 'elementary' level - that appropriate for undergraduates beginning or completing their studies of the topic, or for Master's students - and the very rapid developments that have taken and are still taking place, which quickly age some of the very good text books produced over the last decade or so. This book reflects the authors' experience in teaching one and two semester undergraduate and graduate courses in Digital Image Processing, Digital Image Analysis, Machine Vision, Pattern Recognition and Intelligent Robotics at their respective institutions.

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications PDF Author: Eduardo Bayro Corrochano
Publisher: Springer Science & Business Media
ISBN: 3642102670
Category : Computers
Languages : en
Pages : 1082

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Book Description
This book constitutes the refereed proceedings of the 14th Iberoamerican Congress on Pattern Recognition, CIARP 2009, held in Guadalajara, Mexico, in November 2009. The 64 revised full papers presented together with 44 posters were carefully reviewed and selected from 187 submissions. The papers are organized in topical sections on image coding, processing and analysis; segmentation, analysis of shape and texture; geometric image processing and analysis; analysis of signal, speech and language; document processing and recognition; feature extraction, clustering and classification; statistical pattern recognition; neural networks for pattern recognition; computer vision; video segmentation and tracking; robot vision; intelligent remote sensing, imagery research and discovery techniques; intelligent computing for remote sensing imagery; as well as intelligent fusion and classification techniques.

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications PDF Author: Ruben Vera-Rodriguez
Publisher: Springer
ISBN: 3030134695
Category : Computers
Languages : en
Pages : 1001

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Book Description
This book constitutes the refereed post-conference proceedings of the 23rd Iberoamerican Congress on Pattern Recognition, CIARP 2018, held in Madrid, Spain, in November 2018 The 112 papers presented were carefully reviewed and selected from 187 submissions The program was comprised of 6 oral sessions on the following topics: machine learning, computer vision, classification, biometrics and medical applications, and brain signals, and also on: text and character analysis, human interaction, and sentiment analysis

Computer Vision – ACCV 2020

Computer Vision – ACCV 2020 PDF Author: Hiroshi Ishikawa
Publisher: Springer Nature
ISBN: 3030695328
Category : Computers
Languages : en
Pages : 733

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Book Description
The six volume set of LNCS 12622-12627 constitutes the proceedings of the 15th Asian Conference on Computer Vision, ACCV 2020, held in Kyoto, Japan, in November/ December 2020.* The total of 254 contributions was carefully reviewed and selected from 768 submissions during two rounds of reviewing and improvement. The papers focus on the following topics: Part I: 3D computer vision; segmentation and grouping Part II: low-level vision, image processing; motion and tracking Part III: recognition and detection; optimization, statistical methods, and learning; robot vision Part IV: deep learning for computer vision, generative models for computer vision Part V: face, pose, action, and gesture; video analysis and event recognition; biomedical image analysis Part VI: applications of computer vision; vision for X; datasets and performance analysis *The conference was held virtually.

Computer Vision Using Local Binary Patterns

Computer Vision Using Local Binary Patterns PDF Author: Matti Pietikäinen
Publisher: Springer Science & Business Media
ISBN: 0857297481
Category : Mathematics
Languages : en
Pages : 213

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Book Description
The recent emergence of Local Binary Patterns (LBP) has led to significant progress in applying texture methods to various computer vision problems and applications. The focus of this research has broadened from 2D textures to 3D textures and spatiotemporal (dynamic) textures. Also, where texture was once utilized for applications such as remote sensing, industrial inspection and biomedical image analysis, the introduction of LBP-based approaches have provided outstanding results in problems relating to face and activity analysis, with future scope for face and facial expression recognition, biometrics, visual surveillance and video analysis. Computer Vision Using Local Binary Patterns provides a detailed description of the LBP methods and their variants both in spatial and spatiotemporal domains. This comprehensive reference also provides an excellent overview as to how texture methods can be utilized for solving different kinds of computer vision and image analysis problems. Source codes of the basic LBP algorithms, demonstrations, some databases and a comprehensive LBP bibliography can be found from an accompanying web site. Topics include: local binary patterns and their variants in spatial and spatiotemporal domains, texture classification and segmentation, description of interest regions, applications in image retrieval and 3D recognition - Recognition and segmentation of dynamic textures, background subtraction, recognition of actions, face analysis using still images and image sequences, visual speech recognition and LBP in various applications. Written by pioneers of LBP, this book is an essential resource for researchers, professional engineers and graduate students in computer vision, image analysis and pattern recognition. The book will also be of interest to all those who work with specific applications of machine vision.