SmartPhoto: A Resource-Aware Crowdsourcing Approach for Image Sensing with Smartphones

Abstract— Photos obtained via crowdsourcing can be used in many critical applications. Due to the limitations of communication bandwidth, storage, and processing capability, it is a challenge to transfer the huge amount of crowdsourced photos. To address this problem, we propose a framework, called SmartPhoto, to quantify the quality (utility) of crowdsourced photos based on the accessible geographical and geometrical information (called metadata) including the smartphone’s orientation, position, and all related parameters of the built-in camera. From the metadata, we can infer where and how the photo is taken, and then only transmit the most useful photos. Four optimization problems regarding the tradeoffs between photo utility and resource constraints, namely Max-Utility,
online Max-Utility, Min-Selection, and Min-Selection with k-coverage, are studied. Efficient lgorithms are proposed and their performance bounds are theoretically proved. < final year projects >