documentation/outline_specification/ops.bib
@inproceedings{ulrich2000appearance,
author = {Ulrich, Iwan and Nourbakhsh, Illah},
booktitle = {AAAI/IAAI},
citeulike-article-id = {13506279},
keywords = {mmp},
pages = {866--871},
posted-at = {2015-02-02 09:43:39},
priority = {2},
title = {{Appearance-based obstacle detection with monocular color vision}},
year = {2000},
annote={\textit{Describes an appearance-based obstacle detection approach that focusses on the use of pixel colour within a sub-region of an image to distinguish between the ground, and obstacles.}}
}
@book{guzel2011vision,
author = {Guzel, Mehmet S. and Bicker, Robert},
booktitle = {Recent Advances in Mobile Robotics},
citeulike-article-id = {13506276},
editor = {Topalov, Andon},
isbn = {978-953-307-909-7},
keywords = {mmp},
posted-at = {2015-02-02 09:40:29},
priority = {2},
publisher = {INTECH Open Access Publisher},
title = {{Vision based obstacle avoidance techniques}},
year = {2011},
annote={\textit{Clear analysis and comparison of various approaches to obstacle avoidance using vision-based techniques. Includes an insightful discussion on the key strengths and weaknesses of feature-based and appearance-based algorithms for obstacle tracking.}}
}
@inproceedings{1315094,
author = {Nister, D. and Naroditsky, O. and Bergen, J.},
booktitle = {Computer Vision and Pattern Recognition, 2004. CVPR 2004. Proceedings of the 2004 IEEE Computer Society Conference on},
citeulike-article-id = {13503197},
citeulike-linkout-0 = {http://dx.doi.org/10.1109/CVPR.2004.1315094},
doi = {10.1109/CVPR.2004.1315094},
keywords = {mmp},
month = jun,
posted-at = {2015-01-28 16:04:25},
priority = {2},
title = {{Visual odometry}},
url = {http://dx.doi.org/10.1109/CVPR.2004.1315094},
volume = {1},
year = {2004},
annote={\textit{Describes an alternative approach to vision-based obstacle avoidance utilising two cameras over a monocular vision system to provide depth information of the environment (i.e. stereo vision) that is later used to determine the position of obstacles.}}
}
@inproceedings{378190,
author = {Cipolla, R. and Okamoto, Y. and Kuno, Y.},
booktitle = {Computer Vision, 1993. Proceedings., Fourth International Conference on},
citeulike-article-id = {13503191},
citeulike-linkout-0 = {http://dx.doi.org/10.1109/ICCV.1993.378190},
doi = {10.1109/ICCV.1993.378190},
keywords = {mmp},
month = may,
pages = {374--382},
posted-at = {2015-01-28 16:01:50},
priority = {2},
title = {{Robust structure from motion using motion parallax}},
url = {http://dx.doi.org/10.1109/ICCV.1993.378190},
year = {1993},
annote={\textit{Provides a clear insight into the general use of parallax observed within an image scene in the inference of the ego motion of a robot through an environment.}}
}
@inproceedings{campbell2004techniques,
author = {Campbell, Jason and Sukthankar, Rahul and Nourbakhsh, Illah},
booktitle = {Intelligent Robots and Systems, 2004.(IROS 2004). Proceedings. 2004 IEEE/RSJ International Conference on},
citeulike-article-id = {13503175},
keywords = {mmp},
organization = {IEEE},
pages = {3704--3711},
posted-at = {2015-01-28 15:58:52},
priority = {2},
title = {{Techniques for evaluating optical flow for visual odometry in extreme terrain}},
volume = {4},
year = {2004},
annote={\textit{Provides clear information on practical approaches for evaluating the success of vision-based systems. While the paper focusses on the evaluation of optical-flow, many of the points discussed could be applied in the general case (e.g. open loop vs. closed loop testing).}}
}
@article{fazli2011robust,
author = {Fazli, Saeid and Dehnavi, Hajar M. and Moallem, Payman},
citeulike-article-id = {13500737},
journal = {Optical Review},
keywords = {mmp},
number = {6},
pages = {415--422},
posted-at = {2015-01-25 12:01:27},
priority = {0},
publisher = {Springer},
title = {{A robust negative obstacle detection method using seed-growing and dynamic programming for visually-impaired/blind persons}},
volume = {18},
year = {2011},
annote={\textit{Describes a novel approach to improving the accuracy and speed of traditional vision-based negative obstacle avoidance algorithms using of problem-solving models (dynamic programming) with a seed-growing algorithm.}}
}
@inproceedings{hld,
author = {Morton, Ryan D. and Olson, E.},
booktitle = {Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ International Conference on},
citeulike-article-id = {13500726},
citeulike-linkout-0 = {http://dx.doi.org/10.1109/IROS.2011.6095142},
doi = {10.1109/IROS.2011.6095142},
keywords = {mmp},
month = sep,
pages = {1579--1584},
posted-at = {2015-01-25 11:58:40},
priority = {2},
title = {{Positive and negative obstacle detection using the HLD classifier}},
url = {http://dx.doi.org/10.1109/IROS.2011.6095142},
year = {2011},
annote={\textit{Proposes an approach to inferring precise details of an approaching positive or negative obstacle through the interrogation of 3D point-cloud data (gathered using a LiDAR scanner) using a Height, Length and Depth (HLD) classifier.}}
}
@inproceedings{campbell2005robust,
author = {Campbell, Jason and Sukthankar, Rahul and Nourbakhsh, Illah and Pahwa, Aroon},
booktitle = {Robotics and Automation, 2005. ICRA 2005. Proceedings of the 2005 IEEE International Conference on},
citeulike-article-id = {13500723},
keywords = {mmp},
organization = {IEEE},
pages = {3421--3427},
posted-at = {2015-01-25 11:56:54},
priority = {0},
title = {{A robust visual odometry and precipice detection system using consumer-grade monocular vision}},
year = {2005},
annote={\textit{Highly informative paper describing an approach for inferring the presence of positive and negative obstacles in a scene, utilising the effects that motion parallex can cause to optical flow vectors of tracked features.}}
}