Mr. Michael Smith Profile

Michael Smith

at Univ. Laval

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Proceedings Article | 17 September 2018 Presentation + Paper

Field-of-view enhancement for commercially available active imaging camera using time-of-flight technology

Anne-Sophie Poulin-Girard, Michael Smith, Mathieu Gagnon, Marc-Antoine Legault, Simon Thibault

Proceedings Volume 10745, 1074503 (2018) https://doi.org/10.1117/12.2321336

KEYWORDS: Cameras, Infrared cameras, Imaging systems, Sensors, Time of flight cameras, Infrared imaging, Modulation transfer functions, Time of flight imaging, Infrared sensors, 3D modeling

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Active imaging techniques have been, and will remain relevant as an integral part of the sensor network needed in mobile robotics navigation, most commonly with the use of LiDARs. For close range applications, time-of-flight (TOF) cameras are an alternative to more expensive LiDARs. The Kinect v2 (Kinect for XboxOne) has been used frequently as a range imaging camera in machine vision research because of its low cost and good performance. For mobile robotics applications moving at low speed, a larger field of view than the original (70° X 60°) would be desirable to increase awareness of the surroundings, and also detect other moving objects in the trajectory.

Our main goal is therefore to increase the Kinect v2 field of view while keeping its main feature of depth measurements. A simple but effective solution consists in using a conversion lens to increase the ray collection angle before the rays enter the IR camera. Depth measurements remain possible from each pixel using TOF with the Kinect v2 modulated signal, provided the field of illumination matches the field of view. A trade-off has to be made between accuracy of depth measurement, optical performance and field of view/illumination enhancement. Therefore, we modified a Kinect v2 to characterize its optical performances and evaluate its relevancy for applications requiring accurate knowledge of the 3D surroundings.

A field of view improvement of the Kinect v2 and other similar TOF cameras could offer an alternative at minimal cost for depth measurements in machine vision, specifically in mobile robotics research where object detection and mapping tasks are frequently carried out.

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