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Título | Object Detection for Functional Assessment Applications |
Tipo de publicación | Conference Paper |
Año de publicación | 2023 |
Autores | Melino-Carrero, A, Nieva-Suarez, A, Losada-Gutiérrez, C, Marron-Romera, M, Guardiola-Luna, I, Baeza-Mas, J |
Idioma de publicación | English |
Conference Name | International Conference on Engineering Applications of Neural Networks |
Páginas | Accepted for publication |
Conference Location | Leon (Spain) |
Fecha de publicación | 06/2023 |
Palabras clave | Functional assessment, Human-Object Interaction, object detection, Occupational therapy |
Resumen | This paper presents a proposal for object detection as a first stage for the analysis of Human-Object Interaction (HOI) in the context of automated functional assessment. The proposed system is based in a two-step strategy, thus, in the first stage there are detected the people in the scene, as well as large objects (table, chairs, etc.) using a pre-trained YOLOv8. Then, there is defined a ROI around each person that is processed using a custom YOLO to detect small elements (forks, plates, spoons, etc.). Since there are no large image datasets that include all the objects of interest, there has also been compiled a new dataset including images from different sets, and improving the available labels. |