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With the rapid development of indoor positioning and intelligent robotics technologies, fine-grained location services are approaching. The existing 3D indoor information acquisition and expression methods of furniture are complex and inefficient and cannot meet the needs of high-precision indoor location services. Therefore, this paper proposed a parameterized crowdsourcing method for indoor 3D furniture data based on a model library. This method used a set of classifications and codes of indoor furniture facilities, constructed multilevel feature expression parameters for indoor objects, established an indoor 3D furniture facility model library, and obtained 3D indoor furniture data using the “template + parameters” crowdsourcing method. An indoor furniture data organization model based on 3D parameters was established to manage, store and update indoor furniture facility data. In order to verify the effectiveness of the method, a 3D crowdsourcing system was developed. In the system, the building model was used as the basis for labeling, and the indoor room was the basic unit. The system realizes the functions of indoor scene browsing, 3D furniture data labeling and fast updating. The experimental results prove the feasibility of the crowdsourcing method and provide a new idea for using crowdsourcing for existing indoor 3D data.

A crowdsourcing method for 3D furniture based on parameterized template