Publication

Information-gain view planning for free-form object reconstruction with a 3D ToF camera

Conference Article

Conference

International Conference on Advanced Concepts for Intelligent Vision Systems (ACIVS)

Edition

14th

Pages

36-47

Doc link

http://dx.doi.org/10.1007/978-3-642-33140-4_4

File

Download the digital copy of the doc pdf document

Abstract

Active view planning for gathering data from an unexplored 3D complex scenario is a hard and still open problem in the computer vision community. In this paper, we present a general task-oriented approach based on an information-gain maximization that easily deals with such a problem. Our approach consists of ranking a given set of possible actions, based on their task-related gains, and then executing the best-ranked action to move the required sensor.



An example of how our approach behaves is demonstrated by applying it over 3D raw data for real-time volume modelling of complex-shaped objects. Our setting includes a calibrated 3D time-of-flight (ToF) camera mounted on a 7 degrees of freedom (DoF) robotic arm. Noise in the sensor data acquisition, which is too often ignored, is here explicitly taken into account by computing an uncertainty matrix for each point, and refining this matrix each time the point is seen again. Results show that, by always choosing the most informative view, a complete model of a 3D free-form object is acquired and also that our method achieves a good compromise between speed and precision.

Categories

active vision, computer vision, intelligent robots, manipulators, robot vision.

Author keywords

next best view, active sensor planning, information gain

Scientific reference

S. Foix, S. Kriegel, S. Fuchs, G. Alenyà and C. Torras. Information-gain view planning for free-form object reconstruction with a 3D ToF camera, 14th International Conference on Advanced Concepts for Intelligent Vision Systems, 2012, Brno, Czech Republic, in Advanced Concepts for Intelligent Vision Systems, Vol 7517 of Lecture Notes in Computer Science, pp. 36-47, 2012, Springer.