IR depth from stereo for autonomous navigation

John S. Zelek; Marc Holbein; Kiana Hajebi; Daniel C. Asmar; David Cheng

doi:10.1117/12.604151

12 May 2005 IR depth from stereo for autonomous navigation

John S. Zelek, Marc Holbein, Kiana Hajebi, Daniel C. Asmar, David Cheng

Proceedings Volume 5784, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XVI; (2005) https://doi.org/10.1117/12.604151
Event: Defense and Security, 2005, Orlando, Florida, United States

Abstract

Visual computations such as depth-from-stereo are highly dependent on edges and textures for the process of image correspondence. IR images typically lack the necessary detail for producing dense depth maps, however, sparse maps may be adequate for autonomous obstacle avoidance. We have constructed an IR stereo head for eventual UGV and UAV night time navigation. In order to calibrate the unit, we have constructed a thermal calibration checkerboard. We show that standard stereo camera calibration based on a checkerboard developed for calibrating visible spectrum cameras can also be used for calibrating an IR stereo pair, with of course hot/cold squares used as opposed to black/white squares. Once calibrated, the intrinsic and extrinsic parameters for each camera provide the absolute depth value if a left-right correspondence can be established. Given the general texture-less characteristic of IR imagery, selecting key salient features that are left-right stable and tractable is key for producing a sparse depth map. IR imagery, like visible and range maps is highly spatially correlated and a dense map can be obtained from a sparse map via propagation. Preliminary results from salient IR feature detection are investigated as well.

Citation Download Citation

John S. Zelek, Marc Holbein, Kiana Hajebi, Daniel C. Asmar, and David Cheng "IR depth from stereo for autonomous navigation", Proc. SPIE 5784, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XVI, (12 May 2005); https://doi.org/10.1117/12.604151

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available