We present the results of using Hidden Markov Models (HMMs) for automatic segmentation and recognition of user motions. Previous work on recognition of user intent with man/machin...
C. Sean Hundtofte, Gregory D. Hager, Allison M. Ok...
Most work in human activity recognition is limited to relatively simple behaviors like sitting down, standing up or other dramatic posture changes. Very little has been achieved i...
Changes in motion properties of trajectories provide useful cues for modeling and recognizing human activities. We associate an event with significant changes that are localized in...
Naresh P. Cuntoor, B. Yegnanarayana, Rama Chellapp...
Recent studies have shown that the perception of natural movements--in the sense of being "humanlike"--depends on both joint and task space characteristics of the movemen...
Although the technical skills of pupils are quite high, the current approach to gain media literacy still focusses on updating software applying skills, rather than exploring the ...
Daniela Reimann, Michael Herczeg, Thomas Winkler, ...