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Incorporating wheelchair users in people detection

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Abstract

A wheelchair users detector is presented to extend people detection, providing a more general solution to detect people in environments such as houses adapted for independent and assisted living, hospitals, healthcare centers and senior residences. A wheelchair user model is incorporated in a detector whose detections are afterwards combined with the ones obtained using traditional people detectors (we define these as standing people detectors). We have trained a model for classical (DPM) and two for modern (Faster-RCNN and YOLOv3) detection algorithms, to compare their performance. Besides the extensibility proposed with respect to people detection, a dataset of video sequences has been recorded in a real in-door senior residence environment containing wheelchairs users and standing people and it has been released together with the associated ground-truth.

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Acknowledgments

This work has been partially supported by the Spanish government under the project TEC2014-53176-R (HAVideo) and by the Spanish Government FPU grant programme (Ministerio de Educación, Cultura y Deporte).

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Authors and Affiliations

  1. Video Processing and Understanding Lab (VPULab), Universidad Autónoma de Madrid, Madrid, 28049, Spain

    Rafael Martín-Nieto, Alvaro García-Martín & José M. Martínez

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  1. Rafael Martín-Nieto
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  2. Alvaro García-Martín
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  3. José M. Martínez
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Correspondence to Rafael Martín-Nieto.

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Martín-Nieto, R., García-Martín, A. & Martínez, J.M. Incorporating wheelchair users in people detection. Multimed Tools Appl 78, 14109–14127 (2019). https://doi.org/10.1007/s11042-018-6822-7

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