Computational complexity of art gallery problems
IEEE Transactions on Information Theory
Two algorithms for constructing a binary tree from its traversals
Information Processing Letters
Parallel and serial heuristics for the minimum set cover problem
The Journal of Supercomputing
Introduction to Algorithms
Automatic extraction of Irregular Network digital terrain models
SIGGRAPH '79 Proceedings of the 6th annual conference on Computer graphics and interactive techniques
The coverage problem in a wireless sensor network
WSNA '03 Proceedings of the 2nd ACM international conference on Wireless sensor networks and applications
Near-optimal sensor placements in Gaussian processes
ICML '05 Proceedings of the 22nd international conference on Machine learning
On the optimal placement of multiple visual sensors
Proceedings of the 4th ACM international workshop on Video surveillance and sensor networks
A Delaunay Triangulation based method for wireless sensor network deployment
Computer Communications
Polygon-based texture mapping for cyber city 3D building models
International Journal of Geographical Information Science
Using location based social networks for quality-aware participatory data transfer
Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Location Based Social Networks
A case study of participatory data transfer for urban temperature monitoring
W2GIS'11 Proceedings of the 10th international conference on Web and wireless geographical information systems
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We envision participatory texture documentation (PTD) as a process in which a group of participants (dedicated individuals and/or general public) with camera-equipped mobile phones participate in collaborative/social collection of the urban texture information. PTD enables inexpensive, scalable and high resolution urban texture documentation. PTD is implemented in two steps. In the first step, minimum number of points in the urban environment are selected from which collection of maximum urban texture is possible. This step is called viewpoint selection . In the next step, the selected viewpoints are assigned to users (based on their preferences and constraints) for texture collection. This step is termed viewpoint assignment . In this paper, we focus on the viewpoint selection problem. We prove that this problem is NP-hard, and accordingly, propose a scalable (and efficient) heuristic with approximation guarantee for viewpoint selection. We study, profile and verify our proposed solution by extensive experiments.