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Object Detection for Functional Assessment Applications

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Engineering Applications of Neural Networks (EANN 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1826))

Abstract

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. The proposal has been evaluated in the novel dataset, and in different images acquired in the area in which the functional assessment is performed, obtaining promising results.

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Acknowledgements

This work has been partially supported by the Spanish Ministry of Science and Innovation MICINN/AEI/10.13039/501100011033 under projects EYEFUL-UAH (PID2020-113118RB-C31) and ATHENA (PID2020-115995RB-I00), by CAM under project CONCORDIA (CM/JIN/2021-015), and by UAH under projects ARGOS+ (PIUAH21/IA-016) and METIS (PIUAH22/IA-037).

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Authors and Affiliations

  1. Universidad de Alcalá, Department of Electronics, Edificio Politécnico, Ctra. Madrid-Barcelona Km 33,600, 28805, Alcalá de Henares, Spain

    Alessandro Melino-Carrero, Álvaro Nieva Suárez, Cristina Losada-Gutierrez, Marta Marron-Romera, Irene Guardiola Luna & Javier Baeza-Mas

Authors
  1. Alessandro Melino-Carrero
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  2. Álvaro Nieva Suárez
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  3. Cristina Losada-Gutierrez
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  4. Marta Marron-Romera
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  5. Irene Guardiola Luna
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  6. Javier Baeza-Mas
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Corresponding author

Correspondence to Alessandro Melino-Carrero .

Editor information

Editors and Affiliations

  1. Democritus University of Thrace, Xanthi, Greece

    Lazaros Iliadis

  2. University of Piraeus, Piraeus, Greece

    Ilias Maglogiannis

  3. University of Leon, León, Spain

    Serafin Alonso

  4. Teesside University, Middlesbrough, UK

    Chrisina Jayne

  5. University of the West of England, Bristol, UK

    Elias Pimenidis

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Melino-Carrero, A., Suárez, Á.N., Losada-Gutierrez, C., Marron-Romera, M., Luna, I.G., Baeza-Mas, J. (2023). Object Detection for Functional Assessment Applications. In: Iliadis, L., Maglogiannis, I., Alonso, S., Jayne, C., Pimenidis, E. (eds) Engineering Applications of Neural Networks. EANN 2023. Communications in Computer and Information Science, vol 1826. Springer, Cham. https://doi.org/10.1007/978-3-031-34204-2_28

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  • DOI: https://doi.org/10.1007/978-3-031-34204-2_28

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  • Online ISBN: 978-3-031-34204-2

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