Title :
Long exposure localization in darkness using consumer cameras
Author :
Milford, Michael J. ; Turner, Irem ; Corke, Peter
Author_Institution :
Sch. of Electr. Eng. & Comput. Sci., Queensland Univ. of Technol., Brisbane, QLD, Australia
Abstract :
In this paper we demonstrate passive vision-based localization in environments more than two orders of magnitude darker than the current benchmark using a $100 webcam and a $500 camera. Our approach uses the camera´s maximum exposure duration and sensor gain to achieve appropriately exposed images even in unlit night-time environments, albeit with extreme levels of motion blur. Using the SeqSLAM algorithm, we first evaluate the effect of variable motion blur caused by simulated exposures of 132 ms to 10000 ms duration on localization performance. We then use actual long exposure camera datasets to demonstrate day-night localization in two different environments. Finally we perform a statistical analysis that compares the baseline performance of matching unprocessed grayscale images to using patch normalization and local neighborhood normalization - the two key SeqSLAM components. Our results and analysis show for the first time why the SeqSLAM algorithm is effective, and demonstrate the potential for cheap camera-based localization systems that function across extreme perceptual change.
Keywords :
SLAM (robots); cameras; computer vision; image matching; statistical analysis; SeqSLAM algorithm; camera maximum exposure duration; cheap camera-based localization systems; consumer cameras; local neighborhood normalization; long exposure localization; magnitude order; passive vision-based localization; patch normalization; perceptual change; sensor gain; simultaneous localization and mapping; statistical analysis; unlit night-time environments; unprocessed grayscale image matching; Image resolution; Lighting; Navigation; Robot sensing systems; Visualization; Webcams;
Conference_Titel :
Robotics and Automation (ICRA), 2013 IEEE International Conference on
Conference_Location :
Karlsruhe
Print_ISBN :
978-1-4673-5641-1
DOI :
10.1109/ICRA.2013.6631105