Jigsaw: Indoor Floor Plan Reconstruction via Mobile Crowdsensing ∗ Ruipeng Gao1, Mingmin Zhao1,TaoYe1,FanYe1,2, Yizhou Wang1, Kaigui Bian1, Tao Wang1, Xiaoming Li1 EECS School, Peking University, Beijing 100871, China1 ECE Department, Stony Brook University, Stony Brook, NY 11794, USA2 {gaoruipeng, zhaomingmin, pkuleonye, yefan1, yizhou.wang, bkg, wangtao, lxm}@pku.edu.cn,
[email protected] ABSTRACT 10,000 locations worldwide, which is only a small fraction The lack of floor plans is a critical reason behind the current of millions of indoor environments (e.g., airports, train sporadic availability of indoor localization service. Service stations, shopping malls, museums and hospitals) on the providers have to go through effort-intensive and time- Earth. One major obstacle to ubiquitous coverage is the consuming business negotiations with building operators, or lack of indoor floor plans. Service providers have to conduct hire dedicated personnel to gather such data. In this paper, effort-intensive and time-consuming business negotiations we propose Jigsaw, a floor plan reconstruction system that with building owners or operators to collect the floor plans, leverages crowdsensed data from mobile users. It extracts or wait for them to voluntarily upload such data. Neither is the position, size and orientation information of individual conducive to large scale coverage in short time. landmark objects from images taken by users. It also obtains In this paper, we propose Jigsaw, which leverages the spatial relation between adjacent landmark objects from crowdsensed data from mobile users to construct the inertial sensor data, then computes the coordinates and floor plans of complex indoor environments. It avoids orientations of these objects on an initial floor plan.