Indonesian Journal of Electrical Engineering and Computer Science
Vol 13, No 1: January 2019

Development of framework for detecting smoking scene in video clips

Poonam Ghuli (Department of CSE, RVCE)
Shashank B N (Department of CSE, RVCE)
Athri G Rao (Department of CSE, RVCE)



Article Info

Publish Date
01 Jan 2019

Abstract

According to Global Adult Tobacco Survey 2016-17, 61.9% of people quitting tobacco the reason was the warnings displayed on the product covers. The focus of this paper is to automatically display warning messages in video clips. This paper explains the development of a system to automatically detect the smoking scenes using image recognition approach in video clips and then add the warning message to the viewer.  The approach aims to detect the cigarette object using Tensorflow’s object detection API. Tensorflow is an open source software library for machine learning provided by Google which is broadly used in the field image recognition. At present, Faster R-CNN with Inception ResNet is theTensorflow’s slowest but most accurate model. Faster R-CNN with Inception Resnet v2 model is used to detect smoking scenes by training the model with cigarette as an object.

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