SCIA '09 Proceedings of the 16th Scandinavian Conference on Image Analysis
Combined GKLT Feature Tracking and Reconstruction for Next Best View Planning
Proceedings of the 31st DAGM Symposium on Pattern Recognition
View Planning for 3D Reconstruction Using Time-of-Flight Camera Data
Proceedings of the 31st DAGM Symposium on Pattern Recognition
An Information Roadmap Method for Robotic Sensor Path Planning
Journal of Intelligent and Robotic Systems
Dynamic view planning by effective particles for three-dimensional tracking
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on human computing
Information-driven sensor path planning by approximate cell decomposition
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Nodes Placement for Optimizing Coverage of Visual Sensor Networks
PCM '09 Proceedings of the 10th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
A new approach to the automatic planning of inspection of 3D industrial parts
ACIVS'07 Proceedings of the 9th international conference on Advanced concepts for intelligent vision systems
FGN based telecommunication traffic models
WSEAS Transactions on Computers
Target tracking for mobile robot platforms via object matching and background anti-matching
Robotics and Autonomous Systems
Robotics and Computer-Integrated Manufacturing
Active vision in robotic systems: A survey of recent developments
International Journal of Robotics Research
An autonomous six-DOF eye-in-hand system for in situ 3D object modeling
International Journal of Robotics Research
A new automatic planning of inspection of 3D industrial parts by means of visual system
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
Active planning for underwater inspection and the benefit of adaptivity
International Journal of Robotics Research
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A novel method is proposed in this paper for automatic acquisition of three-dimensional (3-D) models of unknown objects by an active vision system, in which the vision sensor is to be moved from one viewpoint to the next around the target to obtain its complete model. In each step, sensing parameters are determined automatically for incrementally building the 3-D target models. The method is developed by analyzing the target's trend surface, which is the regional feature of a surface for describing the global tendency of change. While previous approaches to trend analysis are usually focused on generating polynomial equations for interpreting regression surfaces in three dimensions, this paper proposes a new mathematical model for predicting the unknown area of the object surface. A uniform surface model is established by analyzing the surface curvatures. Furthermore, a criterion is defined to determine the exploration direction, and an algorithm is developed for determining the parameters of the next view. Implementation of the method is carried out to validate the proposed method.