Title: Efficient image retrievals using generalised Gaussian mixture model

Authors: Anuradha Padala; Srinivas Yarramalle; M.H.M. Krishna Prasad

Addresses: Department of Computer Science and Engineering, Gitam University, Visakhapatnam, 530045, India ' Department of Information Technology, Gitam University, Visakhapatnam, 530045, India ' Department of Computer Science and Engineering, JNTUK, Kakinada, 533003, India

Abstract: The advancements in technology drifted the individuals towards the usage of modern devices and as a result, the usage of web services has increased exponentially. As a result, the quantity of multimedia data accessed and stored across the internet is growing swiftly. Online money transactions, purchases, tenders and many other applications, such as messaging among specific groups were made possible. The usage of social networking sites have gained popularity due to its capability of sharing the videos and audios along with messaging, however, retrieving the most relevant videos is a challenging task among these networking groups. In this paper, a concept of audio tagging is used and the relevant videos are retrieved efficiently. The generalised GMM distribution is used as classifier and MFCC features are used to identify the voices associated with the videos.

Keywords: voice tagging; retrieval; generalised GMM; MFCC; Flicker.

DOI: 10.1504/IJCVR.2017.086281

International Journal of Computational Vision and Robotics, 2017 Vol.7 No.5, pp.605 - 610

Received: 23 Apr 2015
Accepted: 13 Oct 2015

Published online: 27 Jun 2017 *

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