| 主权项 |
1. A method for automatic recognition of human activity, comprising the steps of:
decomposing a human activity into a plurality of fundamental component attributes needed to perform the human activity, wherein the human activity is included in a training set of activities; defining ontologies of fundamental component attributes from the plurality of the fundamental component attributes identified during said decomposing step for each of a plurality of different targeted activities; converting a data stream, the data stream captured during a performance by a human of a performed activity, into a sequence of fundamental component attributes; and classifying the performed activity as one of the plurality of different targeted activities based on a closest match of the sequence of fundamental component attributes obtained during said converting step to at least a part of one of the ontologies of fundamental component attributes defined during said defining step, wherein the performed activity is not included in the training set of activities, the classifying comprising selecting only unseen classes in an attribute space; wherein each of the fundamental component attributes is defined from a sequence of features, and further comprising the step of extracting features from the data stream with computations in at least one of time domain and frequency domain; and wherein the data stream provides a time-sequence of features, and wherein, during said classifying step, a feature at each time slice of the data stream is compared to features of the fundamental component attributes at a corresponding time slice within the ontologies to determine a closest match. |
