Welcome to Central Library, SUST
Amazon cover image
Image from Amazon.com
Image from Google Jackets

Motion History Images for Action Recognition and Understanding [electronic resource] / by Md. Atiqur Rahman Ahad.

By: Contributor(s): Material type: TextTextSeries: SpringerBriefs in Computer SciencePublisher: London : Springer London : Imprint: Springer, 2013Description: XVI, 116 p. 34 illus. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781447147305
Subject(s): Additional physical formats: Printed edition:: No titleDDC classification:
  • 006.4 23
LOC classification:
  • Q337.5
  • TK7882.P3
Online resources:
Contents:
Introduction -- Action Representation -- Motion History Image -- Action Datasets and MHI.
In: Springer eBooksSummary: Human action analysis and recognition is a relatively mature field, yet one which is often not well understood by students and researchers.  The large number of possible variations in human motion and appearance, camera viewpoint, and environment, present considerable challenges.  Some important and common problems remain unsolved by the computer vision community. However, many valuable approaches have been proposed over the past decade, including the motion history image (MHI) method. This method has received significant attention, as it offers greater robustness and performance than other techniques. This work presents a comprehensive review of these state-of-the-art approaches and their applications, with a particular focus on the MHI method and its variants.
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
No physical items for this record

Introduction -- Action Representation -- Motion History Image -- Action Datasets and MHI.

Human action analysis and recognition is a relatively mature field, yet one which is often not well understood by students and researchers.  The large number of possible variations in human motion and appearance, camera viewpoint, and environment, present considerable challenges.  Some important and common problems remain unsolved by the computer vision community. However, many valuable approaches have been proposed over the past decade, including the motion history image (MHI) method. This method has received significant attention, as it offers greater robustness and performance than other techniques. This work presents a comprehensive review of these state-of-the-art approaches and their applications, with a particular focus on the MHI method and its variants.

There are no comments on this title.

to post a comment.