Using Inter-Feature-Line Consistencies for Sequence-Based Object Recognition
Abstract
An image sequence-based framework for appearance-based object recognition is proposed in this paper. Compared with the methods of using a single view for object recognition, inter-frame consistencies can be exploited in a sequence-based method, so that a better recognition performance can be achieved. We use the nearest feature line method (NFL) [8] to model each object. The NFL method is extended in this paper by further integrating motion-continuity information between features lines in a probabilistic framework. The associated recognition task is formulated as maximizing an a posteriori probability measure. The recognition problem is then further transformed to a shortest-path searching problem, and a dynamic-programming technique is used to solve it.
Cite
Text
Chen and Chen. "Using Inter-Feature-Line Consistencies for Sequence-Based Object Recognition." European Conference on Computer Vision, 2004. doi:10.1007/978-3-540-24670-1_9Markdown
[Chen and Chen. "Using Inter-Feature-Line Consistencies for Sequence-Based Object Recognition." European Conference on Computer Vision, 2004.](https://mlanthology.org/eccv/2004/chen2004eccv-using/) doi:10.1007/978-3-540-24670-1_9BibTeX
@inproceedings{chen2004eccv-using,
title = {{Using Inter-Feature-Line Consistencies for Sequence-Based Object Recognition}},
author = {Chen, Jiun-Hung and Chen, Chu-Song},
booktitle = {European Conference on Computer Vision},
year = {2004},
pages = {108-120},
doi = {10.1007/978-3-540-24670-1_9},
url = {https://mlanthology.org/eccv/2004/chen2004eccv-using/}
}