TUTCRIS - Tampereen teknillinen yliopisto


The MOBISERV-AIIA eating and drinking multi-view database for vision-based assisted living



JulkaisuJournal of Information Hiding and Multimedia Signal Processing
TilaJulkaistu - 1 maaliskuuta 2015
OKM-julkaisutyyppiA1 Alkuperäisartikkeli


Assisted living has a particular social importance in most developed societies, due to the increased life expectancy of the general population and the ensuing ageing problems. It has also importance for the provision of improved home care in cases of disabled persons or persons suffering from certain diseases that have high social impact. In this context, the development of computer vision systems capable to identify human eating and drinking activity can be really useful in order to prevent undernourishment/malnutrition and dehydration in a smart home environment targeting to extend independent living of older persons in the early stage of dementia. In this paper, we first describe the human centered interface specifications and implementations for such a system, which can be supported by ambient intelligence and robotic technologies. We, subsequently, describe a multi-view eating and drinking activity recognition database that has been created in order to facilitate research towards this direction. The database has been created by using four cameras in order to produce multi-view videos, each depicting one of twelve persons having a meal, resulting to a database size equal to 59.68 hours in total. Various types of meals have been recorded, i.e., breakfast, lunch and fast food. Moreover, the persons have different sizes, clothing and are of different sex. The database has been annotated in a frame base in terms of person ID and activity class. We hope that such a database will serve as a benchmark data set for computer vision researchers in order to devise methods targeting to this important application.