Harnessing Collective Differences in Crowdsourcing Behaviour for Mass Photogrammetry of 3D Cultural Heritage

Disorganised and self-organised crowdsourcing activities that harness collective behaviours to achieve a specific level of performance and task completeness are not well understood. Such phenomena become indistinct when highly varied environments are present, particularly for crowdsourcing photogrammetry-based 3D models. Mass photogrammetry can democratise traditional close-range photogrammetry procedures by outsourcing image acquisition tasks to a crowd of non-experts to capture geographically scattered 3D objects. To improve public engagement, we need to understand how individual behaviour in collective efforts work in traditional disorganised crowdsourcing and how it can be organised for better performance. This research aims to investigate the effectiveness of disorganised and self-organised collaborative crowdsourcing. It examines the collaborative dynamics among participants and the trends we could leverage if team structures were incorporated. Two scenarios were proposed and constructed: asynchronous crowdsourcing, which implicitly aggregates isolated contributions from disorganised individuals; and synchronous collaborative crowdsourcing, which assigns participants into a crowd-based self-organised team. Our experiment demonstrated that a self-organised team working in synchrony can effectively improve crowdsourcing photogrammetric 3D models in terms of model completeness and user experience. Through our study, we demonstrated that this crowdsourcing mechanism can provide a social context where participants can exchange information via implicit communication, and collectively build a shared mental model that pertains to their responsibilities and task goals. It stimulates participants' prosocial motivation and reinforces their commitment. With more time and effort invested, their positive sense of ownership increases, fostering higher dedication and better contribution. Our findings shed further light on the potentials of adopting team structures to encourage effective collaborations in conventionally individual-based voluntary crowdsourcing settings, especially in the digital heritage domain.