Visual crowdsensing (VCS), which leverages built-in cameras of smart devices to attain informative and comprehensive sensing of interesting targets, has become a predominant sensing paradigm of mobile crowdsensing (MCS). Compared to MCS tasks using other sensing modalities, VCS faces numerous unique issues, such as multi-dimensional coverage needs, data redundancy identification and elimination, low-cost transmission, as well as high data processing cost. This paper characterizes the concepts, unique features, and novel application areas of VCS, and investigates its challenges and key techniques. A generic framework for VCS systems is then presented, followed by discussions about the future directions of crowdsourced picture transmission and the experimental setup in VCS system evaluation.
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Han et al. (2017) studied this question.
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