Novel Planning-based Algorithms for Human Motion Prediction
| Autor: | Dizan Vasquez |
|---|---|
| Přispěvatelé: | Vasquez, Dizan, Robots coopératifs et adaptés à la présence humaine en environnements dynamiques (CHROMA), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-CITI Centre of Innovation in Telecommunications and Integration of services (CITI), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA) |
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
0209 industrial biotechnology
Computational complexity theory Computer science media_common.quotation_subject Computation 02 engineering and technology Machine learning computer.software_genre Behavior learning and modeling 020901 industrial engineering & automation 0202 electrical engineering electronic engineering information engineering [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO] Motion planning Function (engineering) Fast marching method media_common business.industry [INFO.INFO-RB] Computer Science [cs]/Robotics [cs.RO] Robotics Motion prediction Eye tracking 020201 artificial intelligence & image processing Artificial intelligence State (computer science) business Algorithm computer |
| Zdroj: | ICRA IEEE Conference on Robotics and Automation IEEE Conference on Robotics and Automation, May 2016, Stockholm, Sweden |
| Popis: | International audience; — Human motion prediction from visual tracking is a challenging problem with a wide array of applications such as robotics, video surveillance and situation understanding. Recently, planning-based methods –which assume that people move by planning over a cost function– have emerged as one of the most promising alternatives. Nevertheless, state of the art planning based algorithms have shortcomings regarding their computational complexity and ability to predict for arbitrary time intervals. This paper addresses these shortcomings by leveraging alternative planning techniques (Fast Marching Method) and formulating efficient algorithms for goal estimation and full spatiotemporal prediction with lower complexity than comparable approaches. In preliminary experiments, the proposed method significantly outperforms the accuracy of the current state-of-the-art approach while reducing the computation time by a factor of 30 using a parallel version of our algorithm. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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