Matches in SemOpenAlex for { <https://semopenalex.org/work/W4386869577> ?p ?o ?g. }
Showing items 1 to 64 of
64
with 100 items per page.
- W4386869577 endingPage "1" @default.
- W4386869577 startingPage "1" @default.
- W4386869577 abstract "Falls have been widely recognized as one of the most dangerous incidents for the elderly and other people with mobility limitations. This problem has attracted wide scientific interest, which has led to several investigations based on non-vision wearable sensors and static cameras. We investigate the challenge of fall detection and recognition using egocentric wearable cameras, which besides portability and affordability, capture visual information that can be further leveraged for a broad set of lifelogging applications. In this work, five volunteers were equipped with two cameras each, one attached to the neck and the other to the waist. They were asked to simulate four kinds of falls and nine types of non-falls. The newly collected dataset consists of 5858 short video clips, which we make available online. The proposed approach is a late fusion methodology that combines spatial and motion descriptors along with deep features extracted by a pre-trained convolutional neural network. For the spatial and deep features, we consider the similarity of such features between frames in regular intervals of a given time window. In this way, it is the transition between such frames that are encoded in our approach, while the actual scene content does not play a role. We design several experiments to investigate the best camera location and performance for indoor and outdoor activities and employ leave-one-subject-out cross validation to test the generalization ability of our approach. For the fall detection (i.e. two-class) problem, our approach achieves 91.8% accuracy, 93.6% sensitivity and 89.2% specificity." @default.
- W4386869577 created "2023-09-20" @default.
- W4386869577 creator A5012188684 @default.
- W4386869577 creator A5027008332 @default.
- W4386869577 creator A5027326994 @default.
- W4386869577 creator A5042918332 @default.
- W4386869577 date "2023-01-01" @default.
- W4386869577 modified "2023-09-27" @default.
- W4386869577 title "Fall detection with a non-intrusive and first-person vision approach" @default.
- W4386869577 doi "https://doi.org/10.1109/jsen.2023.3314828" @default.
- W4386869577 hasPublicationYear "2023" @default.
- W4386869577 type Work @default.
- W4386869577 citedByCount "0" @default.
- W4386869577 crossrefType "journal-article" @default.
- W4386869577 hasAuthorship W4386869577A5012188684 @default.
- W4386869577 hasAuthorship W4386869577A5027008332 @default.
- W4386869577 hasAuthorship W4386869577A5027326994 @default.
- W4386869577 hasAuthorship W4386869577A5042918332 @default.
- W4386869577 hasConcept C103278499 @default.
- W4386869577 hasConcept C108583219 @default.
- W4386869577 hasConcept C115961682 @default.
- W4386869577 hasConcept C149635348 @default.
- W4386869577 hasConcept C150594956 @default.
- W4386869577 hasConcept C153180895 @default.
- W4386869577 hasConcept C154945302 @default.
- W4386869577 hasConcept C177264268 @default.
- W4386869577 hasConcept C199360897 @default.
- W4386869577 hasConcept C2776151529 @default.
- W4386869577 hasConcept C31972630 @default.
- W4386869577 hasConcept C41008148 @default.
- W4386869577 hasConcept C63000827 @default.
- W4386869577 hasConcept C81363708 @default.
- W4386869577 hasConceptScore W4386869577C103278499 @default.
- W4386869577 hasConceptScore W4386869577C108583219 @default.
- W4386869577 hasConceptScore W4386869577C115961682 @default.
- W4386869577 hasConceptScore W4386869577C149635348 @default.
- W4386869577 hasConceptScore W4386869577C150594956 @default.
- W4386869577 hasConceptScore W4386869577C153180895 @default.
- W4386869577 hasConceptScore W4386869577C154945302 @default.
- W4386869577 hasConceptScore W4386869577C177264268 @default.
- W4386869577 hasConceptScore W4386869577C199360897 @default.
- W4386869577 hasConceptScore W4386869577C2776151529 @default.
- W4386869577 hasConceptScore W4386869577C31972630 @default.
- W4386869577 hasConceptScore W4386869577C41008148 @default.
- W4386869577 hasConceptScore W4386869577C63000827 @default.
- W4386869577 hasConceptScore W4386869577C81363708 @default.
- W4386869577 hasLocation W43868695771 @default.
- W4386869577 hasOpenAccess W4386869577 @default.
- W4386869577 hasPrimaryLocation W43868695771 @default.
- W4386869577 hasRelatedWork W2731899572 @default.
- W4386869577 hasRelatedWork W2999805992 @default.
- W4386869577 hasRelatedWork W3011074480 @default.
- W4386869577 hasRelatedWork W3116150086 @default.
- W4386869577 hasRelatedWork W3133861977 @default.
- W4386869577 hasRelatedWork W4200173597 @default.
- W4386869577 hasRelatedWork W4291897433 @default.
- W4386869577 hasRelatedWork W4311401716 @default.
- W4386869577 hasRelatedWork W4312417841 @default.
- W4386869577 hasRelatedWork W4321369474 @default.
- W4386869577 isParatext "false" @default.
- W4386869577 isRetracted "false" @default.
- W4386869577 workType "article" @default.