Assessment of gait normality using a depth camera and mirrors
This work addresses gait assessment for potential medical or rehabilitation applications, but it is incremental as it builds on existing depth sensing techniques with minor feature innovations.
The paper tackled the problem of assessing gait normality by using a depth camera and mirrors to capture motion, representing it as enhanced depth maps, and extracting two feature types for localized points and posture symmetry, which were combined into scores to evaluate gait; the method was tested on 6 simulated abnormal gaits.
This paper presents an initial work on assessment of gait normality in which the human body motion is represented by a sequence of enhanced depth maps. The input data is provided by a system consisting of a Time-of-Flight (ToF) depth camera and two mirrors. This approach proposes two feature types to describe characteristics of localized points of interest and the level of posture symmetry. These two features are processed on a sequence of enhanced depth maps with the support of a sliding window to provide two corresponding scores. The gait assessment is finally performed based on a weighted combination of these two scores. The evaluation is performed by experimenting on 6 simulated abnormal gaits.