A Mechanism of Automatic 3D Object Modeling
IEEE Transactions on Pattern Analysis and Machine Intelligence
Active shape models—their training and application
Computer Vision and Image Understanding
Planning for complete sensor coverage in inspection
Computer Vision and Image Understanding
A Solution to the Next Best View Problem for Automated Surface Acquisition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Which Slightly Different View is the Right One?
CAIP '99 Proceedings of the 8th International Conference on Computer Analysis of Images and Patterns
Face Model Adaptation using Robust Matching and Active Appearance Models
WACV '02 Proceedings of the Sixth IEEE Workshop on Applications of Computer Vision
Dynamic learning of action patterns for object acquisition
International Journal of Intelligent Systems Technologies and Applications
Survey and analysis of multimodal sensor planning and integration for wide area surveillance
ACM Computing Surveys (CSUR)
Using Multiple Hypotheses to Improve Depth-Maps for Multi-View Stereo
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Consistent parameterization and statistical analysis of human head scans
The Visual Computer: International Journal of Computer Graphics - Special Issue 3D Physiological Human
CAIP '09 Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns
View planning and automated data acquisition for three-dimensional modeling of complex sites
Journal of Field Robotics - Three-Dimensional Mapping, Part 2
Can you see me now? sensor positioning for automated and persistent surveillance
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Recognizing large isolated 3-D objects through next view planning using inner camera invariants
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A next-best-view system for autonomous 3-D object reconstruction
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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In order to provide sufficient information for the 3D reconstruction of a single, static and known type object, this paper proposes measure indexes to evaluate the information amount and a camera planning method to guide the search of the optimal camera positions. The planning method is based on Statistical Deformation Model (SDM) which is generated from Point Distribution Model (PDM) by the Principal Component Analysis (PCA) method. The position from which the individual factor coefficients are observed clearly and the principal shape features are identified distinctly is the best viewpoint. The observed times of landmark are used to exclude the redundancy among views. So, in an iteration process new SDM is repeatedly computed to pick out the optimal viewpoints until all the landmarks are observed sufficiently. Therefore abundant information with the minimum redundancy is provided by fewer cameras, and an experiment which layout cameras for foot reconstruction was demonstrated.