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Benefits of Gaussian Convolution in Gait Recognition
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Datum
2018
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Köllen Druck+Verlag GmbH
Zusammenfassung
The first and still popular approach to gait recognition applies computer vision techniques
to appearance-based features of walking patterns. More recently, wearable sensors have become
attractive. The accelerometer is the most used one, being embedded in widespread mobile devices.
Related techniques do not suffer for problems like occlusion and point of view, but for intra-subject
variations caused by walking speed, ground type, shoes, etc. However, we can often recognize a
person from the walking pattern, and this stimulates to search for robust features, able to sufficiently
characterize this trait. This paper presents some preliminary experiments using the convolution with
Gaussian kernels to extract relevant gait elements. The experiments use the large ZJU-gaitacc public
dataset, and achieve improved results compared with previous works exploiting the same dataset.