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3 July 2014 Detection of potential mosquito breeding sites based on community sourced geotagged images
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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.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ankit Agarwal, Usashi Chaudhuri, Subhasis Chaudhuri, and Guna Seetharaman "Detection of potential mosquito breeding sites based on community sourced geotagged images", Proc. SPIE 9089, Geospatial InfoFusion and Video Analytics IV; and Motion Imagery for ISR and Situational Awareness II, 90890M (3 July 2014);


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