Open Access3D CAPTURING PERFORMANCES OF LOW-COST RANGE SENSORS FOR MASS-MARKET APPLICATIONS
Author(s) -
Gabriele Guidi,
Sara Gonizzi,
Laura Loredana Micoli
Publication year - 2016
Publication title -
the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.264
H-Index - 71
eISSN - 1682-1777
pISSN - 1682-1750
DOI - 10.5194/isprs-archives-xli-b5-33-2016
Subject(s) - computer science , range (aeronautics) , implementation , gesture , focus (optics) , automotive industry , controller (irrigation) , tracking (education) , computer vision , artificial intelligence , computer hardware , real time computing , engineering , agronomy , physics , optics , biology , programming language , aerospace engineering , psychology , pedagogy
Since the advent of the first Kinect as motion controller device for the Microsoft XBOX platform (November 2010), several similar\udactive and low-cost range sensing devices have been introduced on the mass-market for several purposes, including gesture based\udinterfaces, 3D multimedia interaction, robot navigation, finger tracking, 3D body scanning for garment design and proximity sensors\udfor automotive. However, given their capability to generate a real time stream of range images, these has been used in some projects\udalso as general purpose range devices, with performances that for some applications might be satisfying. This paper shows the working\udprinciple of the various devices, analyzing them in terms of systematic errors and random errors for exploring the applicability of them\udin standard 3D capturing problems. Five actual devices have been tested featuring three different technologies: i) Kinect V1 by\udMicrosoft, Structure Sensor by Occipital, and Xtion PRO by ASUS, all based on different implementations of the Primesense sensor;\udii) F200 by Intel/Creative, implementing the Realsense pattern projection technology; Kinect V2 by Microsoft, equipped with the\udCanesta TOF Camera. A critical analysis of the results tries first of all to compare them, and secondarily to focus the range of\udapplications for which such devices could actually work as a viable solution