A Comprehensive Vision-Based Gait Data Collection Framework with a Systematic Multi-Camera Placement Strategy

Şahan, Pınar Güner; Akkaya, Ilgar; Şahan, İbrahim; Şahin, Suhap

doi:10.2478/acss-2025-0017

Abstract

Systematic collection of gait data directly affects the reliability of gait analysis. Therefore, the first step that should be given importance in gait analysis is to ensure that the data collected is of high quality and reliable. Optimising and standardising the data collection process is a critical requirement that increases the success of the analysis. This study proposes a systematic multi-camera placement strategy and data processing process to collect gait data in real time with RGB cameras for gait recognition and analysis applications. The proposed method provides an end-to-end framework from the physical setup of the data collection environment to the data processing steps. The camera placement strategy aims to maximise the visibility of all body parts by capturing the participant’s body from different directions during walking. The results of three different methods used for silhouette extraction from the acquired videos were compared. Furthermore, a video-based approach was used to calculate participants’ walking speeds. Theoretical and practical information provided regarding the data collection and analysis process is detailed to guide future studies. In this respect, the paper is aimed to be a guiding study for researchers working in the related field.

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A Comprehensive Vision-Based Gait Data Collection Framework with a Systematic Multi-Camera Placement Strategy

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