Accession Number:

AD1038225

Title:

Bag-of-Audio-Words Approach for Multimedia Event Classification

Descriptive Note:

Conference Paper

Corporate Author:

SRI International Menlo Park United States

Personal Author(s):

• Pancoast, Stephanie
• Akbacak,Murat

Report Date:

2012-09-13

Pagination or Media Count:

4.0

Abstract:

With the popularity of online multimedia videos, there has been much interest in recent years in acoustic event detection and classification for the improvement of online video search. The audio component of a video has the potential to contribute significantly to multimedia event classification. Recent research in audio document classification has drawn parallels to text and image document retrieval by employing what is referred to as the bag-of-audio words BoAW method. Compared to supervised approaches where audio concept detectors are trained using annotated data and extracted labels are used as low level features for multimedia event classification. The BoAW approach extracts audio concepts in an unsupervised fashion. Hence this method has the advantage that it can be employed easily for a new set of audio concepts in multimedia videos without going through a laborious annotation effort. In this paper, we explore variations of the BoAW method and present results on NIST 2011 multimedia event detection MED dataset.

Descriptors:

• classification
• multimedia
• detection
• audio tones
• automated speech recognition
• histograms

Subject Categories:

• Information Science

Distribution Statement:

APPROVED FOR PUBLIC RELEASE