1.

Record Nr.

UNINA9910299854403321

Autore

Spehr Jens

Titolo

On Hierarchical Models for Visual Recognition and Learning of Objects, Scenes, and Activities [[electronic resource] /] / by Jens Spehr

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015

ISBN

3-319-11325-9

Edizione

[1st ed. 2015.]

Descrizione fisica

1 online resource (210 p.)

Collana

Studies in Systems, Decision and Control, , 2198-4182 ; ; 11

Disciplina

006.3

006.37

006.4

006.6

Soggetti

Robotics

Automation

Computational intelligence

Optical data processing

Pattern recognition

Robotics and Automation

Computational Intelligence

Image Processing and Computer Vision

Pattern Recognition

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references.

Nota di contenuto

Introduction -- Probabilistic Graphical Models -- Hierarchical Graphical Models -- Learning of Hierarchical Models.-Object Recognition -- Human Pose Estimation -- Scene Understanding for Intelligent Vehicles -- Conclusion.

Sommario/riassunto

In many computer vision applications, objects have to be learned and recognized in images or image sequences. This book presents new probabilistic hierarchical models that allow an efficient representation of multiple objects of different categories, scales, rotations, and views. The idea is to exploit similarities between objects and object parts in order to share calculations and avoid redundant information.



Furthermore inference approaches for fast and robust detection are presented. These new approaches combine the idea of compositional and similarity hierarchies and overcome limitations of previous methods. Besides classical object recognition the book shows the use for detection of human poses in a project for gait analysis. The use of activity detection is presented for the design of environments for ageing, to identify activities and behavior patterns in smart homes. In a presented project for parking spot detection using an intelligent vehicle, the proposed approaches are used to hierarchically model the environment of the vehicle for an efficient and robust interpretation of the scene in real-time.