Efficient viewpoint assignment for urban texture documentation

We envision participatory texture documentation (PTD) as a process in which a group of users (dedicated individuals and/or general public) with camera-equipped mobile phones participate in collaborative collection of urban texture information. PTD enables inexpensive, scalable and high resolution urban texture documentation. We have proposed to implement PTD in two steps [10]. At the first step, termed viewpoint selection, a minimum number of points in the urban environment are selected from which the texture of the entire urban environment (the part visible to cameras) can be collected/captured. At the second step, called viewpoint assignment, the selected viewpoints are assigned to the participating users such that given a limited number of users with various constraints (e.g., restricted available time) users can collectively capture the maximum amount of texture information within a limited time interval. In this paper, we focus on the viewpoint assignment problem. We first prove that this problem is an NP-hard problem, and therefore, the optimal solution for viewpoint assignment fails to scale as the extent of the urban environment and the number of participating users grow. Subsequently, we propose a family of heuristics for efficient viewpoint assignment to reduce the assignment running time while ensuring an almost complete texture collection. We study, profile and verify our proposed solutions comparatively by both rigorous analysis and extensive experiments.