ImgPricing: Everyone Can Earn Proper Rewards by Simply Taking Photos

A high-quality and large-scale image collection is a fundamental demand in the 3D reconstruction. Crowdsourcing can help us collect lots of diversified images. However, it is not easy to attract people to do this task due to their self-interest. Moreover, the collected images are quality-varying. Those low-quality images may disturb the performance of reconstruction. To avoid low-quality images and lead participants to collect high-quality data, we take images quality into account when allocating rewards. The rewards of participants should be proportionable with their contribution. In this paper, we propose a pricing mechanism, called ImgPricing, to determine the reward of participants in 3D reconstruction system. We model the process of image collection as a cooperative game, and regard each participant's contribution and corresponding image quality as critical factors when allocating rewards. ImgPricing differs from traditional pricing schemes, such as Shapley value, as it introduces the image sequence as an indispensable factor. Finally, we implement our design on the Android platform and evaluate its performance. We use some metrics, such as computational efficiency, fairness and anti-interference, to evaluate ImgPricing and compare with other traditional schemes. Our analyses show ImgPricing is superior to others in terms of computational efficiency and fairness.