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Lin et al., 2025 - Google Patents

EgoFall: A First-Person View Fall Detection System

Lin et al., 2025

Document ID
2866595240376761061
Author
Lin W
Chu E
Lee C
Publication year
Publication venue
2025 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

External Links

Snippet

Fall detection is crucial for elderly care, as over 30 million older adults experience falls annually, according to the World Health Organization. Most current fall detection systems rely on surveillance cameras to identify sudden posture changes that may indicate a fall …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

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    • G06K9/00221—Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
    • G06K9/00268—Feature extraction; Face representation
    • G06K9/00281—Local features and components; Facial parts ; Occluding parts, e.g. glasses; Geometrical relationships
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
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    • G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G06K9/00771—Recognising scenes under surveillance, e.g. with Markovian modelling of scene activity
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    • G06K9/00362—Recognising human body or animal bodies, e.g. vehicle occupant, pedestrian; Recognising body parts, e.g. hand
    • G06K9/00369—Recognition of whole body, e.g. static pedestrian or occupant recognition
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
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