Title :
A Method for Dynamic Selection of Optimal Depth Measurements Acquisition with Random Access Range Sensors
Author :
Curtis, Paul ; Payeur, Pierre
Author_Institution :
Sch. of Electr. Eng. & Comput. Sci., Univ. of Ottawa, Ottawa, ON, Canada
Abstract :
It is well established that acquiring large amount of range data with vision sensors can quickly lead to important data management challenges where processing capabilities become saturated and preempt full usage of the information available for autonomous systems to make educated decisions. While sub-sampling offers a naive solution for reducing dataset dimension after acquisition, it does not capitalize on the knowledge available in already acquired data to selectively and dynamically drive the acquisition process over the most significant regions in a scene, the latter being generally characterized by variations in depth and surface shape. This paper discusses the development of a formal improvement measure and a method to automatically establish which regions within the field of view of a range sensor would provide the most improvement to a model of the scene if further acquisitions were concentrated in priority over those regions. The proposed algorithm mainly targets applications using random access range sensors, defined as sensors that can acquire depth measurements at specified azimuth and elevation within their field of view. However, the framework is developed to be independent of the range sensing technology used, and is validated with range data acquired from the popular Kinect multi-modal imaging sensor, as well as Neptec,s LMS laser random access range sensor.
Keywords :
data acquisition; decision making; distance measurement; image sensors; natural scenes; random processes; Kinect multimodal imaging sensor; Neptec LMS laser; autonomous system; data management; data processing; decision making; dynamic location selection; field of view; formal improvement measure; optimal depth measurement acquisition; random access range sensor; range data acquisition; range sensing technology; scene; surface shape; vision sensor; Computers; Robots; 3D imaging; Kinect; improvement map; random access range sensors; range measurement; selective sensing; smart sensing;
Conference_Titel :
Computer and Robot Vision (CRV), 2013 International Conference on
Conference_Location :
Regina, SK
Print_ISBN :
978-1-4673-6409-6
DOI :
10.1109/CRV.2013.24