A framework for human action detection via extraction of multimodal features.

N. A., Lili (2009) A framework for human action detection via extraction of multimodal features. International Journal of Image Processing, 3 (2). pp. 73-79. ISSN 1985-2304

Full text not available from this repository.

Abstract

This work discusses the application of an Artificial Intelligence technique called data extraction and a process-based ontology in constructing experimental qualitative models for video retrieval and detection. We present a framework architecture that uses multimodality features as the knowledge representation scheme to model the behaviors of a number of human actions in the video scenes. The main focus of this paper placed on the design of two main components (model classifier and inference engine) for a tool abbreviated as VASD (Video Action Scene Detector) for retrieving and detecting human actions from video scenes. The discussion starts by presenting the workflow of the retrieving and detection process and the automated model classifier construction logic. We then move on to demonstrate how the constructed classifiers can be used with multimodality features for detecting human actions. Finally, behavioral explanation manifestation is discussed. The simulator is implemented in bilingual; Math Lab and C++ are at the backend supplying data and theories while Java handles all front-end GUI and action pattern updating. To compare the usefulness of the proposed framework, several experiments were conducted and the results were obtained by using visual features only (77.89% for precision; 72.10% for recall), audio features only (62.52% for precision; 48.93% for recall) and combined audiovisual (90.35% for precision; 90.65% for recall).

Item Type:Article
Keyword:audiovisual, human action detection, multimodal, hidden markov model.
Subject:Human locomotion-Computer simulation.
Subject:Motion perception (Vision).
Subject:Computer vision.
Faculty or Institute:Faculty of Computer Science and Information Technology
ID Code:12694
Deposited By: Umikalthom Abdullah
Deposited On:24 Nov 2011 05:22
Last Modified:24 Nov 2011 05:22

Repository Staff Only: Edit item detail

Document Download Statistics

This item has been downloaded for since 24 Nov 2011 05:22.

View statistics for "A framework for human action detection via extraction of multimodal features."


Universiti Putra Malaysia Institutional Repository

Universiti Putra Malaysia Institutional Repository is an on-line digital archive that serves as a central collection and storage of scientific information and research at the Universiti Putra Malaysia.

Currently, the collections deposited in the IR consists of Master and PhD theses, Master and PhD Project Report, Journal Articles, Journal Bulletins, Conference Papers, UPM News, Newspaper Cuttings, Patents and Inaugural Lectures.

As the policy of the university does not permit users to view thesis in full text, access is only given to the first 24 pages only.