@inproceedings{
 title = {Optimal Online Data Sampling or How to Hire the Best Secretaries},
 type = {inproceedings},
 year = {2009},
 pages = {292-298},
 websites = {http://cim.mcgill.ca/~yogesh/publications/crv2009.pdf},
 month = {5},
 publisher = {IEEE Computer Society},
 city = {Kelowna, British Columbia},
 id = {930e6be5-f3c1-3669-8daa-37900a3d7234},
 created = {2011-11-19T13:45:48.000Z},
 file_attached = {true},
 profile_id = {2331788d-b144-3e67-ab8c-4abd7ab569c5},
 last_modified = {2019-12-09T12:48:28.335Z},
 read = {true},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Girdhar:CRV:2009},
 source_type = {inproceedings},
 folder_uuids = {a08eb1a8-df79-49b6-a3fe-c57f8c286952,9fe02bf3-6f9f-4e86-a6e6-c0190f2a6db9},
 private_publication = {false},
 abstract = {In this paper we present a framework for automatically generating a visual synopsis of the images observed as a robot follows a trajectory. These ``navigation summaries'' are a set of images that are meant to capture the notable visual events observed by the robot independent of task- specific constraints. These small set of images character- ize the visual appearance of the trajectory of a robot. In our effort to create such summaries we use several different functional criteria while choosing among candidate images and then combine these into a single measurement, tuned to make our decision process approximate the selections that might be made by human observers. Our approach also takes into account the location information of the photos to make sure that the summary images are well distributed in the world. The tuning with respect to human performance is attained by collecting human performance data on a similar task using a web-based interface and setting the parameters of our automated system to match the behaviour of the hu- man observers.},
 bibtype = {inproceedings},
 author = {Girdhar, Yogesh and Dudek, Gregory},
 doi = {10.1109/CRV.2009.30},
 booktitle = {CRV '09: Proceedings of the 2009 Canadian Conference on Computer and Robot Vision}
}

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