Paper: A Privacy-Preserving Wearable Camera Setup for Dietary Event Spotting in Free-Living
The paper will be presented during the PerCom 2018 workshop SmarterAAL - Advanced Technologies for Smarter Assisted Living solutions: Towards an open Smart Home infrastructure in Athens on March 23.
Abstract
We designed a wearable head-mounted egocentric camera setup for dietary data collection in free-living. We addressed the problem of privacy-sensitive image content by fixing a camera on a cap’s visor pointing downwards. Salient content was maintained while drastically constraining unwanted privacy-infringing content. The privacy preservation capability of our setup was compared with literature using a modified privacy-saliency matrix. Furthermore, we implemented a dietary event spotting algorithm to reduce the amount of workload for human operator while performing analysis on a large volume of data. Transfer learning on a deep neural network was employed to perform dietary object detection and, subsequently, dietary event spotting. Average recall performance over 90% suggested the feasibility of the method.
Reference
, "A Privacy-Preserving Wearable Camera Setup for Dietary Event Spotting in Free-Living", Proceedings of the International Conference on Pervasive Computing and Communications (PerCom) Workshops, 2018.
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