1 research outputs found
Detekcja upadku i wybranych akcji na sekwencjach obraz\'ow cyfrowych
In recent years a growing interest on action recognition is observed,
including detection of fall accident for the elderly. However, despite many
efforts undertaken, the existing technology is not widely used by elderly,
mainly because of its flaws like low precision, large number of false alarms,
inadequate privacy preserving during data acquisition and processing. This
research work meets these expectations. The work is empirical and it is
situated in the field of computer vision systems. The main part of the work
situates itself in the area of action and behavior recognition. Efficient
algorithms for fall detection were developed, tested and implemented using
image sequences and wireless inertial sensor worn by a monitored person. A set
of descriptors for depth maps has been elaborated to permit classification of
pose as well as the action of a person. Experimental research was carried out
based on the prepared data repository consisting of synchronized depth and
accelerometric data. The study was carried out in the scenario with a static
camera facing the scene and an active camera observing the scene from above.
The experimental results showed that the developed algorithms for fall
detection have high sensitivity and specificity. The algorithm were designed
with regard to low computational demands and possibility to run on ARM
platforms. Several experiments including person detection, tracking and fall
detection in real-time were carried out to show efficiency and reliability of
the proposed solutions.Comment: PhD Thesis (in Polish