Boston, Robert Trevor
Techniques for orientation independent gait analysis.
University of Southampton, School of Electronics and Computer Science,
Gait recognition algorithms are being increasingly widely researched, however a common
assumption is that the subject will be presented side on to the camera. In practice it may
not be possible to capture data from this view, so a useful gait recognition algorithm
will have to provide a measure of orientation independence.
Three gait recognition algorithms are examined and found to perform poorly with nonnormal
orientation. The complex detail used for recognition can not be translated
between orientations in a holistic silhouette manner.
It is shown that orientation independent features can be extracted using a human model.
The algorithm is developed and tested on live captured data and found to perform better
across orientations than silhouette based approaches. The performance recorded at a
single orientation is lower than that of other approaches, however only the motion of the
subject is currently used for recognition. More accurate motion estimation will increase
performance as will the inclusion of other model based features.
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