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

By: Ahad, Md. Atiqur Rahman [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: SpringerBriefs in Computer Science: Publisher: London : Springer London : Imprint: Springer, 2013Description: XVI, 116 p. 34 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9781447147305.Subject(s): Computer science | Optical pattern recognition | Computer Science | Pattern RecognitionDDC classification: 006.4 Online resources: Click here to access online
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.
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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.

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