NDLI: Development of Supervised Link Mining Using Computer Vision and Pattern Mining Approach

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Development of Supervised Link Mining Using Computer Vision and Pattern Mining Approach

Content Provider	ACM Digital Library
Author	Nandi, G. C. Mishra, Seema
Abstract	The network type we have discussed and explored so far in social network analysis is generated from the nonverbal communication like email logs or chats through electronic medium that provide a rich set of data for analysis of social interactions between people. For getting data for these kind of interactions, we could only rely on that available data that sometimes conduces biased information and we ended up with nonrealistic consequences. Therefore, we propose a new direction to be looked into to explore the interactions in network generated from a means other than electronic communication. This mode of interactions is expected to yield results that must be more realistic. In this paper, we address the important problem of discovering and analysis of social networks with the help of computer vision. A new link mining technique is proposed with the help of computer vision and pattern mining approach which exhibits two processes: extraction of social networks and establishing a link between frequently interacted people captured from the video data. Henceforth, this work is an attempt to extend the scope of applications of computer vision in one more interesting direction. To collect the data, we used the camera that are considered to be a surveillance camera by which a large amount of video data of a group of people is collected routinely. A computer vision approach enabled us to solve this problem at a lower level and with the help of video data obtained from the fixed camera. Camera systems should have the capability for acquiring high-resolution face images of people under challenging conditions. We also perform "opportunistic "face recognition method on captured images in order to store the data of person appearing in the video. Then we present a novel (to the best of our knowledge) frequent pattern mining based approach to solve this problem of identifying the frequent person network. We could observe the connectedness of the work in this chapter with earlier work because the purpose is same as identifying a link between persons involved in communications but the approach of creating an environment is different.
Starting Page	1
Ending Page	6
Page Count	6
File Format	PDF
ISBN	9781450347792
DOI	10.1145/3010089.3010128
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-11-10
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Computer vision Social network analysis Machine learning Pattern mining
Content Type	Text
Resource Type	Article

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