Paper Info
Title
Online Next-Best-View Planning for Accuracy Optimization Using an Extended E-Criterion
Abstract
Next-best-view (NBV) planning is an important aspect for three-dimensional (3D) reconstruction within controlled environments, such as a camera mounted on a robotic arm. NBV methods aim at a purposive 3D reconstruction sustaining predefined goals and limitations. Up to now, literature mainly presents NBV methods for range sensors, model-based approaches or algorithms that address the reconstruction of a finite set of primitives. For this work, we use an intensity camera without active illumination. We present a novel combined online approach comprising feature tracking, 3D reconstruction, and NBV planning that addresses arbitrary unknown objects. In particular we focus on accuracy optimization based on the reconstruction uncertainty. To this end we introduce an extension of the statistical E-criterion to model directional uncertainty, and we present a closed-form, optimal solution to this NBV planning problem. Our experimental evaluation demonstrates the effectivity of our approach using an absolute error measure.
Year
DOI
Venue
2010
10.1109/ICPR.2010.406
ICPR
Keywords
Field
DocType
extended e-criterion,online approach,model-based approach,nbv planning,absolute error measure,directional uncertainty,reconstruction uncertainty,nbv method,nbv planning problem,online next-best-view planning,accuracy optimization,intensity camera,accuracy,feature extraction,planning,robot arm,lead,robotic arm,3d reconstruction,image reconstruction,statistical analysis,three dimensional,sensors
Iterative reconstruction,Computer vision,Robotic arm,Finite set,Computer science,Feature extraction,Artificial intelligence,View planning,Approximation error,Feature tracking,3D reconstruction
Conference
Citations 
PageRank 
References 
16
0.79
7
Authors
3
Name
Order
Citations
PageRank
Michael Trummer1160.79
Christoph Munkelt2384.28
Joachim Denzler3985103.50