Fitting Models to Distributed Representations of Vision
Abstract
Many representations in early vision can be constructed by performing orientation analysis along several sampling dimensions. Texture is often oriented in space, motion is oriented in space-time, and stereo is oriented in spacedisparity. In these modalities, we can construct distributed representations with oriented energy measures used in models of biological vision. Surface models of orientation, velocity, and disparity can easily be fit to distributed representations of texture, motion, and stereo by combining tools of orientation analysis and regularization. We describe base representation construction and model fitting processes
Cite
Text
Niyogi. "Fitting Models to Distributed Representations of Vision." International Joint Conference on Artificial Intelligence, 1995.Markdown
[Niyogi. "Fitting Models to Distributed Representations of Vision." International Joint Conference on Artificial Intelligence, 1995.](https://mlanthology.org/ijcai/1995/niyogi1995ijcai-fitting/)BibTeX
@inproceedings{niyogi1995ijcai-fitting,
title = {{Fitting Models to Distributed Representations of Vision}},
author = {Niyogi, Sourabh A.},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {1995},
pages = {3-9},
url = {https://mlanthology.org/ijcai/1995/niyogi1995ijcai-fitting/}
}