Sciweavers

Share
ICRA
2010
IEEE

MOPED: A scalable and low latency object recognition and pose estimation system

9 years 10 months ago
MOPED: A scalable and low latency object recognition and pose estimation system
— The latency of a perception system is crucial for a robot performing interactive tasks in dynamic human environments. We present MOPED, a fast and scalable perception system for object recognition and pose estimation. MOPED builds on POSESEQ, a state of the art object recognition algorithm, demonstrating a massive improvement in scalability and latency without sacrificing robustness. We achieve this with both algorithmic and architecture improvements, with a novel feature matching algorithm, a hybrid GPU/CPU architecture that exploits parallelism at all levels, and an optimized resource scheduler. Using the same standard hardware, we achieve up to 30x improvement on real-world scenes.
Manuel Martinez, Alvaro Collet, Siddhartha S. Srin
Added 26 Jan 2011
Updated 26 Jan 2011
Type Journal
Year 2010
Where ICRA
Authors Manuel Martinez, Alvaro Collet, Siddhartha S. Srinivasa
Comments (0)
books