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Proceedings Paper

Detection of potential mosquito breeding sites based on community sourced geotagged images
Author(s): Ankit Agarwal; Usashi Chaudhuri; Subhasis Chaudhuri; Guna Seetharaman
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Paper Abstract

Various initiatives have been taken all over the world to involve the citizens in the collection and reporting of data to make better and informed data-driven decisions. Our work shows how the geotagged images collected through the general population can be used to combat Malaria and Dengue by identifying and visualizing localities that contain potential mosquito breeding sites. Our method first employs image quality assessment on the client side to reject the images with distortions like blur and artifacts. Each geotagged image received on the server is converted into a feature vector using the bag of visual words model. We train an SVM classifier on a histogram-based feature vector obtained after the vector quantization of SIFT features to discriminate images containing either a small stagnant water body like puddle, or open containers and tires, bushes etc. from those that contain flowing water, manicured lawns, tires attached to a vehicle etc. A geographical heat map is generated by assigning a specific location a probability value of it being a potential mosquito breeding ground of mosquito using feature level fusion or the max approach presented in the paper. The heat map thus generated can be used by concerned health authorities to take appropriate action and to promote civic awareness.

Paper Details

Date Published: 3 July 2014
PDF: 8 pages
Proc. SPIE 9089, Geospatial InfoFusion and Video Analytics IV; and Motion Imagery for ISR and Situational Awareness II, 90890M (3 July 2014); doi: 10.1117/12.2058121
Show Author Affiliations
Ankit Agarwal, Indian Institute of Technology Bombay (India)
Usashi Chaudhuri, Father Conceicao Rodrigues Institute of Technology (India)
Subhasis Chaudhuri, Indian Institute of Technology Bombay (India)
Guna Seetharaman, Air Force Research Lab. (United States)

Published in SPIE Proceedings Vol. 9089:
Geospatial InfoFusion and Video Analytics IV; and Motion Imagery for ISR and Situational Awareness II
Matthew F. Pellechia; Kannappan Palaniappan; Shiloh L. Dockstader; Paul B. Deignan; Peter J. Doucette; Donnie Self, Editor(s)

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