GestureRecognitionToolkit
Version: 0.2.5
The Gesture Recognition Toolkit (GRT) is a cross-platform, open-source, c++ machine learning library for real-time gesture recognition.
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The Class Label Filter is a useful post-processing module which can remove erroneous or sporadic prediction spikes that may be made by a classifier on a continuous input stream of data. More...
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class | ClassLabelFilter |
The Class Label Filter is a useful post-processing module which can remove erroneous or sporadic prediction spikes that may be made by a classifier on a continuous input stream of data.
For instance, imagine a classifier that correctly outputs the predicted class label of 1 for a large majority of the time that a user is performing gesture 1, but every so often (perhaps due to sensor noise), the classifier outputs the class label of 2. In this instance the class label filter can be used to remove these sporadic prediction values, with the output of the class label filter in this instance being 1.
The Class Label Filter module is controlled through two parameters: the minimum count value and buffer size value. The minimum count sets the minimum number of class label values that must be present in the class labels buffer for that class label value to be output by the Class Label Filter. The size of the class labels buffer is set by the buffer size parameter. If there is more than one type of class label in the buffer then the class label with the maximum number of instances will be output. If the maximum number of instances for any class label in the buffer is less than the minimum count parameter then the Class Label Filter will output the default null rejection class label of 0. The minimum count and buffer size parameters can be set using the setMinimumCount(UINT minimumCount) and setBufferSize(UINT bufferSize) methods.
Definition in file ClassLabelFilter.h.