Dense-Hog-based 3D face tracking for infant pain monitoring

Ronald W.J.J. Saeijs, Walther E. Tjon A Ten, Peter H.N. de With

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

3 Citations (Scopus)
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This paper presents a new algorithm for 3D face tracking intended for clinical infant pain monitoring under challenging conditions. The algorithm uses a cylinder head model and head pose recovery by alignment of dynamically extracted templates based on dense-HOG features. The algorithm is motivated from the application context and compared with a variant based on intensities. The paper reports experimental results on videos of moving infants in hospital who are relaxed or in pain. Results show good short-term tracking behavior for poses up to 50 degrees from upright-frontal, with significantly higher accuracy resulting from the use of dense-HOG features.
Original languageEnglish
Title of host publication2016 IEEE International Conference on Image Processing (ICIP), September 25-28, 2016, Phoenix, Arizona, USA
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Number of pages5
ISBN (Print)978-1-4673-9961-6
Publication statusPublished - 19 Aug 2016
Event23rd IEEE International Conference on Image Processing (ICIP 2016) - Phoenix Convention Center, Phoenix, AZ, United States
Duration: 25 Sept 201628 Sept 2016
Conference number: 23


Conference23rd IEEE International Conference on Image Processing (ICIP 2016)
Abbreviated titleICIP 2016
Country/TerritoryUnited States
CityPhoenix, AZ
Internet address


  • face tracking, pain monitoring, cylinder head model, dense HOG


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