Group and Crowd Behavior for Computer Vision

Group and Crowd Behavior for Computer Vision provides a multidisciplinary perspective on how to solve the problem of group and crowd analysis and modeling, combining insights from the social sciences with technological ideas in computer vision and pattern recognition. The book answers many unresolved issues in group and crowd behavior, with Part One providing an introduction to the problems of analyzing groups and crowds that stresses that they should not be considered as completely diverse entities, but as an aggregation of people. Part Two focuses on features and representations with the aim of recognizing the presence of groups and crowds in image and video data. It discusses low level processing methods to individuate when and where a group or crowd is placed in the scene, spanning from the use of people detectors toward more ad-hoc strategies to individuate group and crowd formations. Part Three discusses methods for analyzing the behavior of groups and the crowd once they have been detected, showing how to extract semantic information, predicting/tracking the movement of a group, the formation or disaggregation of a group/crowd and the identification of different kinds of groups/crowds depending on their behavior. The final section focuses on identifying and promoting datasets for group/crowd analysis and modeling, presenting and discussing metrics for evaluating the pros and cons of the various models and methods. This book gives computer vision researcher techniques for segmentation and grouping, tracking and reasoning for solving group and crowd modeling and analysis, as well as more general problems in computer vision and machine learning. Presents the first book to cover the topic of modeling and analysis of groups in computer vision Discusses the topics of group and crowd modeling from a cross-disciplinary perspective, using social science anthropological theories translated into computer vision algorithms Focuses on group and crowd analysis metrics Discusses real industrial systems dealing with the problem of analyzing groups and crowds

Produk Detail:

  • Author : Vittorio Murino
  • Publisher : Academic Press
  • Pages : 438 pages
  • ISBN : 0128092807
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKGroup and Crowd Behavior for Computer Vision

Group and Crowd Behavior for Computer Vision

Group and Crowd Behavior for Computer Vision
  • Author : Vittorio Murino,Marco Cristani,Shishir Shah,Silvio Savarese
  • Publisher : Academic Press
  • Release : 18 April 2017
GET THIS BOOKGroup and Crowd Behavior for Computer Vision

Group and Crowd Behavior for Computer Vision provides a multidisciplinary perspective on how to solve the problem of group and crowd analysis and modeling, combining insights from the social sciences with technological ideas in computer vision and pattern recognition. The book answers many unresolved issues in group and crowd behavior, with Part One providing an introduction to the problems of analyzing groups and crowds that stresses that they should not be considered as completely diverse entities, but as an aggregation

Computer Vision for Microscopy Image Analysis

Computer Vision for Microscopy Image Analysis
  • Author : Mei Chen
  • Publisher : Academic Press
  • Release : 01 December 2020
GET THIS BOOKComputer Vision for Microscopy Image Analysis

Are you a computer scientist working on image analysis? Are you a biologist seeking tools to process the microscopy data from image-based experiments? Computer Vision for Microscopy Image Analysis provides a comprehensive and in-depth discussion of modern computer vision techniques, in particular deep learning, for microscopy image analysis that will advance your efforts. Progress in imaging techniques has enabled the acquisition of large volumes of microscopy data and made it possible to conduct large-scale, image-based experiments for biomedical discovery. The

Multimodal Behavior Analysis in the Wild

Multimodal Behavior Analysis in the Wild
  • Author : Xavier Alameda-Pineda,Elisa Ricci,Nicu Sebe
  • Publisher : Academic Press
  • Release : 13 November 2018
GET THIS BOOKMultimodal Behavior Analysis in the Wild

Multimodal Behavioral Analysis in the Wild: Advances and Challenges presents the state-of- the-art in behavioral signal processing using different data modalities, with a special focus on identifying the strengths and limitations of current technologies. The book focuses on audio and video modalities, while also emphasizing emerging modalities, such as accelerometer or proximity data. It covers tasks at different levels of complexity, from low level (speaker detection, sensorimotor links, source separation), through middle level (conversational group detection, addresser and addressee identification),

Vision Models for High Dynamic Range and Wide Colour Gamut Imaging

Vision Models for High Dynamic Range and Wide Colour Gamut Imaging
  • Author : Marcelo Bertalmío
  • Publisher : Academic Press
  • Release : 06 November 2019
GET THIS BOOKVision Models for High Dynamic Range and Wide Colour Gamut Imaging

To enhance the overall viewing experience (for cinema, TV, games, AR/VR) the media industry is continuously striving to improve image quality. Currently the emphasis is on High Dynamic Range (HDR) and Wide Colour Gamut (WCG) technologies, which yield images with greater contrast and more vivid colours. The uptake of these technologies, however, has been hampered by the significant challenge of understanding the science behind visual perception. Vision Models for High Dynamic Range and Wide Colour Gamut Imaging provides university

Energy Minimization Methods in Computer Vision and Pattern Recognition

Energy Minimization Methods in Computer Vision and Pattern Recognition
  • Author : Marcello Pelillo,Edwin Hancock
  • Publisher : Springer
  • Release : 23 March 2018
GET THIS BOOKEnergy Minimization Methods in Computer Vision and Pattern Recognition

This volume constitutes the refereed proceedings of the 11th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR 2017, held in Venice, Italy, in October/November 2017. The 37 revised full papers were carefully reviewed and selected from 51 submissions. The papers are organized in topical sections on Clustering and Quantum Methods; Motion and Tracking; Image Processing and Segmentation; Color, Shading and Reflectance of Light; Propagation and Time-evolution; and Inference, Labeling, and Relaxation.

Computer Vision – ECCV 2018

Computer Vision – ECCV 2018
  • Author : Vittorio Ferrari,Martial Hebert,Cristian Sminchisescu,Yair Weiss
  • Publisher : Springer
  • Release : 05 October 2018
GET THIS BOOKComputer Vision – ECCV 2018

The sixteen-volume set comprising the LNCS volumes 11205-11220 constitutes the refereed proceedings of the 15th European Conference on Computer Vision, ECCV 2018, held in Munich, Germany, in September 2018.The 776 revised papers presented were carefully reviewed and selected from 2439 submissions. The papers are organized in topical sections on learning for vision; computational photography; human analysis; human sensing; stereo and reconstruction; optimization; matching and recognition; video attention; and poster sessions.

Artificial Neural Networks and Machine Learning – ICANN 2021

Artificial Neural Networks and Machine Learning – ICANN 2021
  • Author : Igor Farkaš,Paolo Masulli,Sebastian Otte,Stefan Wermter
  • Publisher : Springer Nature
  • Release : 10 September 2021
GET THIS BOOKArtificial Neural Networks and Machine Learning – ICANN 2021

The proceedings set LNCS 12891, LNCS 12892, LNCS 12893, LNCS 12894 and LNCS 12895 constitute the proceedings of the 30th International Conference on Artificial Neural Networks, ICANN 2021, held in Bratislava, Slovakia, in September 2021.* The total of 265 full papers presented in these proceedings was carefully reviewed and selected from 496 submissions, and organized in 5 volumes. In this volume, the papers focus on topics such as computer vision and object detection, convolutional neural networks and kernel methods, deep learning and optimization, distributed and continual learning, explainable methods, few-shot

Deep Learning through Sparse and Low-Rank Modeling

Deep Learning through Sparse and Low-Rank Modeling
  • Author : Zhangyang Wang,Yun Fu,Thomas S. Huang
  • Publisher : Academic Press
  • Release : 11 April 2019
GET THIS BOOKDeep Learning through Sparse and Low-Rank Modeling

Deep Learning through Sparse Representation and Low-Rank Modeling bridges classical sparse and low rank models—those that emphasize problem-specific Interpretability—with recent deep network models that have enabled a larger learning capacity and better utilization of Big Data. It shows how the toolkit of deep learning is closely tied with the sparse/low rank methods and algorithms, providing a rich variety of theoretical and analytic tools to guide the design and interpretation of deep learning models. The development of the

Dynamic Switching State Systems for Visual Tracking

Dynamic Switching State Systems for Visual Tracking
  • Author : Becker, Stefan
  • Publisher : KIT Scientific Publishing
  • Release : 02 December 2020
GET THIS BOOKDynamic Switching State Systems for Visual Tracking

This work addresses the problem of how to capture the dynamics of maneuvering objects for visual tracking. Towards this end, the perspective of recursive Bayesian filters and the perspective of deep learning approaches for state estimation are considered and their functional viewpoints are brought together.

Representations, Analysis and Recognition of Shape and Motion from Imaging Data

Representations, Analysis and Recognition of Shape and Motion from Imaging Data
  • Author : Liming Chen,Boulbaba Ben Amor,Faouzi Ghorbel
  • Publisher : Springer
  • Release : 04 May 2019
GET THIS BOOKRepresentations, Analysis and Recognition of Shape and Motion from Imaging Data

This book constitutes the refereed proceedings of the 7th International Workshop on Representations, Analysis and Recognition of Shape and Motion from Imaging Data, RFMI 2017, held in Savoi, France, in December 2017. The 8 revised full papers and 9 revised short papers presented were carefully reviewed and selected from 23 submissions. The papers are organized in topical sections on analyzing motion data; deep learning on image and shape data; 2D and 3D pattern classification; watermarking, segmentation and deformations.

Spectral Geometry of Shapes

Spectral Geometry of Shapes
  • Author : Jing Hua,Zichun Zhong
  • Publisher : Academic Press
  • Release : 15 January 2020
GET THIS BOOKSpectral Geometry of Shapes

Spectral Geometry of Shapes presents unique shape analysis approaches based on shape spectrum in differential geometry. It provides insights on how to develop geometry-based methods for 3D shape analysis. The book is an ideal learning resource for graduate students and researchers in computer science, computer engineering and applied mathematics who have an interest in 3D shape analysis, shape motion analysis, image analysis, medical image analysis, computer vision and computer graphics. Due to the rapid advancement of 3D acquisition technologies there

Statistical Shape and Deformation Analysis

Statistical Shape and Deformation Analysis
  • Author : Guoyan Zheng,Shuo Li,Gabor Szekely
  • Publisher : Academic Press
  • Release : 23 March 2017
GET THIS BOOKStatistical Shape and Deformation Analysis

Statistical Shape and Deformation Analysis: Methods, Implementation and Applications contributes enormously to solving different problems in patient care and physical anthropology, ranging from improved automatic registration and segmentation in medical image computing to the study of genetics, evolution and comparative form in physical anthropology and biology. This book gives a clear description of the concepts, methods, algorithms and techniques developed over the last three decades that is followed by examples of their implementation using open source software. Applications of statistical

Advanced Concepts for Intelligent Vision Systems

Advanced Concepts for Intelligent Vision Systems
  • Author : Jacques Blanc-Talon,David Helbert,Wilfried Philips,Dan Popescu,Paul Scheunders
  • Publisher : Springer
  • Release : 24 September 2018
GET THIS BOOKAdvanced Concepts for Intelligent Vision Systems

This book constitutes the refereed proceedings of the 19th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2018, held in Poitiers, France, in September 2018. The 52 full papers presented in this volume were carefully reviewed and selected from 91 submissions. They were organized in topical sections named: video analysis; segmentation and classification; remote sending; biometrics; deep learning; coding and compression; and image restauration and reconstruction.

Skeletonization

Skeletonization
  • Author : Punam K Saha,Gunilla Borgefors,Gabriella Sanniti di Baja
  • Publisher : Academic Press
  • Release : 06 June 2017
GET THIS BOOKSkeletonization

Skeletonization: Theory, Methods and Applications is a comprehensive reference on skeletonization, written by the world’s leading researchers in the field. The book presents theory, methods, algorithms and their evaluation, together with applications. Skeletonization is used in many image processing and computer vision applications such as shape recognition and analysis, shape decomposition and character recognition, as well as medical imaging for pulmonary, cardiac, mammographic applications. Part I includes theories and methods unique to skeletonization. Part II includes novel applications including

Image Analysis

Image Analysis
  • Author : Michael Felsberg,Per-Erik Forssén,Ida-Maria Sintorn,Jonas Unger
  • Publisher : Springer
  • Release : 09 July 2019
GET THIS BOOKImage Analysis

This volume constitutes the refereed proceedings of the 21st Scandinavian Conference on Image Analysis, SCIA 2019, held in Norrköping, Sweden, in June 2019. The 40 revised papers presented were carefully reviewed and selected from 63 submissions. The contributions are structured in topical sections on Deep convolutional neural networks; Feature extraction and image analysis; Matching, tracking and geometry; and Medical and biomedical image analysis.​