PT Journal
AU T. Mouats
   N. Aouf
   Angel Sappa
   Cristhian A. Aguilera-Carrasco
   Ricardo Toledo
TI Multi-Spectral Stereo Odometry
SO IEEE Transactions on Intelligent Transportation Systems
JI TITS
PY 2015
BP 1210
EP 1224
VL 16
IS 3
DI 10.1109/TITS.2014.2354731
DE Egomotion estimation; feature matching; multispectral odometry (MO); optical flow; stereo odometry; thermal imagery
AB In this paper, we investigate the problem of visual odometry for ground vehicles based on the simultaneous utilization of multispectral cameras. It encompasses a stereo rig composed of an optical (visible) and thermal sensors. The novelty resides in the localization of the cameras as a stereo setup ratherthan two monocular cameras of different spectrums. To the best of our knowledge, this is the first time such task is attempted. Log-Gabor wavelets at different orientations and scales are used to extract interest points from both images. These are then described using a combination of frequency and spatial information within the local neighborhood. Matches between the pairs of multimodal images are computed using the cosine similarity function basedon the descriptors. Pyramidal Lucas–Kanade tracker is also introduced to tackle temporal feature matching within challenging sequences of the data sets. The vehicle egomotion is computed from the triangulated 3-D points corresponding to the matched features. A windowed version of bundle adjustment incorporatingGauss–Newton optimization is utilized for motion estimation. An outlier removal scheme is also included within the framework to deal with outliers. Multispectral data sets were generated and used as test bed. They correspond to real outdoor scenarios captured using our multimodal setup. Finally, detailed results validating the proposed strategy are illustrated.
ER