@article{
 title = {Non-contact video-based pulse rate measurement on a mobile service robot},
 type = {article},
 year = {2014},
 identifiers = {[object Object]},
 pages = {1056-1062},
 websites = {http://ieeexplore.ieee.org/document/6926392/},
 id = {5818acd6-b7fe-3a79-8fbf-e3bd8ef39ae2},
 created = {2018-07-02T19:08:17.764Z},
 file_attached = {true},
 profile_id = {f18f97b7-60c6-33d4-b944-c08e6c28fa12},
 group_id = {2d721da3-627a-3ca3-862a-cd2d130d920f},
 last_modified = {2018-07-02T19:08:37.564Z},
 read = {true},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Stricker2014},
 folder_uuids = {81855f6c-11eb-4375-a02e-a3cd04030ca0},
 private_publication = {false},
 abstract = {Non-contact image photoplethysmography has gained a lot of attention during the last 5 years. Starting with the work of Verkruysse et al. [1], various methods for estimation of the human pulse rate from video sequences of the face under ambient illumination have been presented. Applied on a mobile service robot aimed to motivate elderly users for physical exercises, the pulse rate can be a valuable information in order to adapt to the users conditions. For this paper, a typical processing pipeline was implemented on a mobile robot, and a detailed comparison of methods for face segmentation was conducted, which is the key factor for robust pulse rate extraction even, if the subject is moving. A benchmark data set is introduced focusing on the amount of motion of the head during the measurement.},
 bibtype = {article},
 author = {Stricker, Ronny and Muller, Steffen and Gross, Horst-Michael},
 journal = {The 23rd IEEE International Symposium on Robot and Human Interactive Communication}
}

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