loading
Documents

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Hao Wang ; Ya Zhang and Zhe Xu

Affiliation: Shanghai Jiao Tong University, China

ISBN: 978-989-758-004-8

Keyword(s): Visual Object Detection, Wide Baseline Matching, Local Image Feature, Spatial Consistency.

Abstract: Local image features show a high degree of repeatability, while their local appearance usually does not bring enough discriminative pattern to obtain a reliable matching. In this paper, we present a new object matching algorithm based on a novel robust estimation of residual consensus and flexible spatial consistency filter. We evaluate the similarity between different homography model via two-parameter integrated Weibull distribution and inlier probabilities estimates, which can select uncontaminated model to help eliminating outliers. Spatial consistency test was encoded by the geometric relationships of domain knowledge in two directions, which is invariant to scale, rotation, and translation especially robust to the flipped image. Experiment results on nature images with clutter background demonstrate our method effectiveness and robustness.

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 100.26.182.28

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Wang, H.; Zhang, Y. and Xu, Z. (2014). Exploring Residual and Spatial Consistency for Object Detection.In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2014) ISBN 978-989-758-004-8, pages 191-197. DOI: 10.5220/0004746801910197

@conference{visapp14,
author={Hao Wang. and Ya Zhang. and Zhe Xu.},
title={Exploring Residual and Spatial Consistency for Object Detection},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2014)},
year={2014},
pages={191-197},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004746801910197},
isbn={978-989-758-004-8},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2014)
TI - Exploring Residual and Spatial Consistency for Object Detection
SN - 978-989-758-004-8
AU - Wang, H.
AU - Zhang, Y.
AU - Xu, Z.
PY - 2014
SP - 191
EP - 197
DO - 10.5220/0004746801910197

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.