Self Calibration of the Fixation Movement of a Stereo Camera Head
Abstract
In this article we show how an active stereo camera head can be made to autonomously learn to fixate objects in space. During fixation, the system performs an initial and a correction saccade. In the learning phase the correction saccade is controlled by a crude pre-wired algorithm, in analogy to a mechanism surmised to exist in the brainstem. A vector-based neural network serves as the adaptive component in our system. A self-organizing fovea improves dramatically the convergence of the learning algorithm and the accuracy of the fixation. As a possible application we describe the visuo-motor coordination of the camera head with an anthropomorphic robot arm.
Cite
Text
Pagel et al. "Self Calibration of the Fixation Movement of a Stereo Camera Head." Machine Learning, 1998. doi:10.1023/A:1007448826336Markdown
[Pagel et al. "Self Calibration of the Fixation Movement of a Stereo Camera Head." Machine Learning, 1998.](https://mlanthology.org/mlj/1998/pagel1998mlj-self/) doi:10.1023/A:1007448826336BibTeX
@article{pagel1998mlj-self,
title = {{Self Calibration of the Fixation Movement of a Stereo Camera Head}},
author = {Pagel, Mike and Maël, Eric and von der Malsburg, Christoph},
journal = {Machine Learning},
year = {1998},
pages = {169-186},
doi = {10.1023/A:1007448826336},
volume = {31},
url = {https://mlanthology.org/mlj/1998/pagel1998mlj-self/}
}