SmartPhoto: A Resource-Aware Crowd Sourcing Approach for ImageSensing With Smart - Coimbatore

ABSTRACT
Photos obtained via crowd sourcing 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 crowd sourced photos. To address this problem, we propose a framework, called Smart Photo, to quantify the quality (utility) of crowd sourced 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 trade offs between photo utility and resource constraints, namely Max-Utility, online Max-Utility, Min-Selection and Min-Selection with k-coverage, are studied. Efficient algorithms are proposed and their performance bounds are theoretically proved. We have implemented Smart Photo in a test bed using Android based smart phones, and proposed techniques to improve the accuracy of the collected metadata by reducing sensor reading errors and solving object occlusion issues. Results based on real implementations and extensive simulations demonstrate the effectiveness of the proposed algorithms.

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