Visual Analysis Of Behaviour: From Pixels To Semantics

Description: Please refer to the section BELOW (and NOT ABOVE) this line for the product details - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Title:Visual Analysis Of Behaviour: From Pixels To SemanticsISBN13:9780857296696ISBN10:0857296698Author:Gong, Shaogang (Author), Xiang, Tao (Author)Description:Demand Continues To Grow Worldwide, From Both Government And Commerce, For Technologies Capable Of Automatically Selecting And Identifying Objecthuman Behaviour This Accessible Textreference Presents A Comprehensive And Unified Treatment Of Visual Analysis Of Behaviour From Computational-Modelling And Algorithm-Design Perspectives The Book Provides In-Depth Discussion On Computer Vision And Statistical Machine Learning Techniques, In Addition To Reviewing A Broad Range Of Behaviour Modelling Problems A Mathematical Background Is Not Required To Understand The Content, Although Readers Will Benefit From Modest Knowledge Of Vectors And Matrices, Eigenvectors And Eigenvalues, Linear Algebra, Optimisation, Multivariate Analysis, Probability, Statistics And Calculus Topics And Features: Provides A Thorough Introduction To The Study And Modelling Of Behaviour, And A Concluding Epilogue; Covers Learning-Group Activity Models, Unsupervised Behaviour Profiling, Hierarchical Behaviour Discovery, Learning Behavioural Context, Modelling Rare Behaviours, And Man-In-The-Loop Active Learning Of Behaviours; Examines Multi-Camera Behaviour Correlation, Person Re-Identification, And Connecting-The-Dots For Global Abnormal Behaviour Detection; Discusses Bayesian Information Criterion, Bayesian Networks, Bag-Of-Words Representation, Canonical Correlation Analysis, Dynamic Bayesian Networks, Gaussian Mixtures, And Gibbs Sampling; Investigates Hidden Conditional Random Fields, Hidden Markov Models, Human Silhouette Shapes, Latent Dirichlet Allocation, Local Binary Patterns, Locality Preserving Projection, And Markov Processes; Explores Probabilistic Graphical Models, Probabilistic Topic Models, Space-Time Interest Points, Spectral Clustering, And Support Vector Machines; Includes A Helpful List Of Acronyms A Valuable Resource For Both Researchers In Computer Vision And Machine Learning, And For Developers Of Commercial Applications, The Book Can Also Serve As A Useful Reference For Postgraduate Students Of Computer Science And Behavioural Science Furthermore, Policymakers And Commercial Managers Will Find This An Informed Guide On Intelligent Video Analytics Systems Binding:Hardcover, HardcoverPublisher:SpringerPublication Date:2011-05-27Weight:1.45 lbsDimensions:1'' H x 9.2'' L x 6.1'' WNumber of Pages:356Language:English

Price: 159.35 USD

Location: USA

End Time: 2024-10-23T17:51:50.000Z

Shipping Cost: 0 USD