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Fig. 1 | Journal of NeuroEngineering and Rehabilitation

Fig. 1

From: Egocentric vision-based detection of surfaces: towards context-aware free-living digital biomarkers for gait and fall risk assessment

Fig. 1

The proposed framework consists of two models: a EgoPlaceNet, which classifies scenes (one \(1080\times 1080\) region for each frame cropped randomly either from right or left corner, the blue square) into indoor and outdoor, and b EgoTerrainNet, with Indoor and Outdoor versions, which classifies two 453\(\times\)453 (red squares) and 1080\(\times\)1080 patches based on the enclosed terrain type

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