1 / 7

BACS Review Meeting

BACS Review Meeting. Summary on the subject Laban Movement Analysis Jörg Rett 17 th – 19 th March 2008 Collège de France, Paris. Overview: Effort & Infrastructure. List of people involved in Laban BACS (changes M1-12 to M13-24) Paid by BACS Joerg Rett PhD Student 1,32

renee
Download Presentation

BACS Review Meeting

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. BACS Review Meeting Summary on the subject Laban Movement Analysis Jörg Rett 17th – 19th March 2008 Collège de France, Paris

  2. Overview: Effort & Infrastructure • List of people involved in Laban BACS (changes M1-12 to M13-24) • Paid by BACS • Joerg Rett PhD Student 1,32 • Luis Santos PhD Student 1,1 • Total 2,42 • Own Resources • Jorge Dias Professor 2,4 • Total 2,4 • Infrastructure involved in Laban BACS (M13 – M24) • Nicole/Laban/testa

  3. WP 5, Task 5.4.2 Goal Computational Laban Movement Analysis (LMA) using the Bayesian framework Problem: The research field of computational Human Movement Analysis is lacking a general underlying modeling language. How to map the features into symbols? How to model human behavior? Solution: A semantic descriptor allowing to recognize a sequence of symbols taken from an alphabet consisting of motion-entities. Benefit: Establish a set of labels for observable human behavior. The possibility to build large databases with labeled training data.

  4. WP 5, Task 5.4.2 Achievements Computational Laban Movement Analysis (LMA) using the Bayesian framework Processes for online classification LMA labels Classified behavior LLF 3-D Points Low Level Feature Computation Bayesian Inference Bayesian Inference Tracking

  5. WP 5, Task 5.4.2 Results – Examples and Demos Move-ment Tracked positions Low-level features Laban descriptors Behavior hypothesis Space Speed Gain Effort.Time Effort.Space Curvature

  6. WP 5, Task 5.4.2 Future Plans and Risks • D5.17FCT-UC/Probayes: • Publication on ‘Computational Laban Movement Analysis based on Vision and 3-D Position Estimation’ T31 • D5.18FCT-UC/Probayes: • Publication on ‘Bayesian Model for Computational Laban Movement Analysis’ T33 • D5.20FCT-UC/Probayes: • Publication on ‘Computational Laban Movement Analysis using Multi-Camera Systems’ T36

  7. WP 5 Summary 1 • Major Achievements during M13-M24 • Computational Laban Movement Analysis based on Vision and 3-D Position Estimation • List of Deliverables • D5.7 (MPS) Report on computational human pose recovery in clutter M18 • Conference • Rett, J., Dias, J.: Human-robot interface with anticipatory characteristics based on Laban Movement Analysis and Bayesian models. In: Proceedings of the IEEE 10th International Conference on Rehabilitation Robotics (ICORR). (2007) • Rett, J., Dias, J.: Human Robot Interaction based on Bayesian Analysis of Human Movements. In: Proceedings of EPIA 07, Lecture Notes in AI, Springer Verlag, Berlin. (2007) • Rett, J. and Dias, J. “Computational Laban Movement Analysis using probability calculus.” In the Proceedings of Workshop on Robotics and Mathematics, RoboMat 2007. • Rett, J. and Dias, J.:”Bayesian models for Laban Movement Analysis used in Human Machine Interaction.” Proceedings of ICRA 2007 Workshop on "Concept Learning for Embodied Agents“. • Major collaborations within BACS • Collaboration between FCT-UC and Probayes concerning the models an joint publications. • Summary of future plans • Computational Laban Movement Analysis using Multi-Camera Systems

More Related