1. A behavior content classification device comprising: image capturing means for capturing a first image including a face of an object person, the first image comprising a second image including a predetermined portion of the face; feature extraction means for extracting features from the second image; a hidden Markov model (HMM) having as input the extracted features and having as output a likelihood for a predetermined behavior content relating to a movement of the predetermined portion; and behavior content classification means for calculating the likelihood using the extracted features and the HMM, and for classifying behavior content relating to the movement of the predetermined portion of the object person based on the calculation result, wherein: the image capturing means comprises: positional relation information acquisition means for acquiring positional relation information between the first image and the second image, and face direction classification means for classifying a face direction of the object person according to the positional relation information, the behavior content classification means further selects the HMM from among a plurality of candidate HMMs based on the classification result of the face direction classification means, the candidate HMMs being generated for a plurality of face directions, and the selected HMM corresponding to the face direction of face direction classification result.