Interactive Adaptation of Real-Time Object Detectors
Title | Interactive Adaptation of Real-Time Object Detectors |
Publication Type | Conference Paper |
Year of Publication | 2014 |
Authors | Göhring, D., Hoffman J., Rodner E., Saenko K., & Darrell T. |
Other Numbers | 3630 |
Abstract | In the following paper, we present a framework forquickly training 2D object detectors for robotic perception. Ourmethod can be used by robotics practitioners to quickly (under30 seconds per object) build a large-scale real-time perceptionsystem. In particular, we show how to create new detectors onthe fly using large-scale internet image databases, thus allowinga user to choose among thousands of available categories tobuild a detection system suitable for the particular roboticapplication. Furthermore, we show how to adapt these modelsto the current environment with just a few in-situ images.Experiments on existing 2D benchmarks evaluate the speed,accuracy, and flexibility of our system. |
URL | https://www.icsi.berkeley.edu/pubs/vision/interactiveadaption14.pdf |
Bibliographic Notes | Proceedings of the IEEE International Conference in Robotics and Automation (ICRA), Hong Kong, China |
Abbreviated Authors | D. Goehring, J. Hoffman, E. Rodner, K. Saenko, and T. Darrell |
ICSI Research Group | Vision |
ICSI Publication Type | Article in conference proceedings |