Principal motion: PCA-based reconstruction of motion histograms

principal motion is the implementation of a reconstruction approach to gesture recognition based on principal components analysis (PCA). The underlying idea is to perform PCA on the frames in each video from the vocabulary, storing the PCA models. Frames in test-videos are projected into the PCA space and reconstructed back using each of the PCA models, one for each gesture in the vocabulary. Next we measure the reconstruction error for each of the models and assign a test video the gesture that obtains the lowest reconstruction error. The rest of this document provides more details about the principal motion object.