Principles of artificial intelligence
Principles of artificial intelligence
A survey of automated visual inspection
Computer Vision and Image Understanding
Autonomous Exploration: Driven by Uncertainty
IEEE Transactions on Pattern Analysis and Machine Intelligence
Active Vision for Complete Scene Reconstruction and Exploration
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Solution to the Next Best View Problem for Automated Surface Acquisition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Occlusions as a Guide for Planning the Next View
IEEE Transactions on Pattern Analysis and Machine Intelligence
View planning for automated three-dimensional object reconstruction and inspection
ACM Computing Surveys (CSUR)
An Information Theoretic Approach for Next Best View Planning in 3-D Reconstruction
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
Two Stage View Planning for Large-Scale Site Modeling
3DPVT '06 Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06)
Efficient Constraint Evaluation Algorithms for Hierarchical Next-Best-View Planning
3DPVT '06 Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06)
Active Sensor Planning for Multiview Vision Tasks
Active Sensor Planning for Multiview Vision Tasks
Optimal view path planning for visual SLAM
SCIA'11 Proceedings of the 17th Scandinavian conference on Image analysis
Covariance propagation and next best view planning for 3d reconstruction
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part II
Active planning for underwater inspection and the benefit of adaptivity
International Journal of Robotics Research
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We propose an approach for acquiring geometric 3D models using cameras mounted on autonomous vehicles and robots. Our method uses structure from motion techniques from computer vision to obtain the geometric structure of the scene. To achieve an efficient goal-driven resource deployment, we develop an incremental approach, which alternates between an accuracy-driven next best view determination and recursive path planning. The next best view is determined by a novel cost function that quantifies the expected contribution of future viewing configurations. A sensing path for robot motion towards the next best view is then achieved by a cost-driven recursive search of intermediate viewing configurations. We discuss some of the properties of our view cost function in the context of an iterative view planning process and present experimental results on a synthetic environment.