Baby-posture classification from pressure-sensor data

Sabri Boughorbel, Fons Bruekers, Jeroen Breebaart

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

Abstract

The activity of babies and more specifically the posture of babies is an important aspect in their safety and development. In this paper, we studied the automatic classification of baby posture using a pressure-sensitive mat. The posture classification problem is formulated as the design of features that describe the pressure patterns induced by the child in combination with generic classifiers. Novel rotation invariant features constructed from high order statistics obtained from the concentric rings around the center of gravity. Non-constant ring radii are used in order to ensure uniform cell areas and therefore equal importance of features. A vote fusion of various generic classifiers is used for classification. Temporal information was shown to improve the classification performance. The obtained results are promising and open new opportunities for applications and further research in the area of baby safety and development.

Original languageEnglish
Title of host publicationProceedings - 2010 20th International Conference on Pattern Recognition, ICPR 2010
Pages556-559
Number of pages4
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event2010 20th International Conference on Pattern Recognition, ICPR 2010 - Istanbul, Turkey
Duration: 23 Aug 201026 Aug 2010

Other

Other2010 20th International Conference on Pattern Recognition, ICPR 2010
CountryTurkey
CityIstanbul
Period23/8/1026/8/10

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ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

Cite this

Boughorbel, S., Bruekers, F., & Breebaart, J. (2010). Baby-posture classification from pressure-sensor data. In Proceedings - 2010 20th International Conference on Pattern Recognition, ICPR 2010 (pp. 556-559). [5597438] https://doi.org/10.1109/ICPR.2010.141