2 research outputs found
Detection of semantic risk situations in lifelog data for improving life of frail people
The automatic recognition of risk situations for frail people is an
urgent research topic for the interdisciplinary artificial intelligence
and multimedia community. Risky situations can be recognized
from lifelog data recorded with wearable devices. In this paper, we
present a new approach for the detection of semantic risk situations
for frail people in lifelog data. Concept matching between general
lifelog and risk taxonomies was realized and tuned AlexNet was
deployed for detection of two semantic risks situations such as risk
of domestic accident and risk of fraud with promising results
Towards Unsupervised Familiar Scene Recognition in Egocentric Videos
Nowadays, there is an upsurge of interest in using lifelogging devices. Such devices generate huge amounts of image data; consequently, the need for automatic methods for analyzing and summarizing these data is drastically increasing. We present a new method for familiar scene recognition in egocentric videos, based on background pattern detection through automatically configurable COSFIRE filters. We present some experiments over egocentric data acquired with the Narrative Clip