Exploring Residual and Spatial Consistency for Object Detection

Hao Wang; Ya Zhang; Zhe Xu

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Paper

Exploring Residual and Spatial Consistency for Object Detection

Topics: Content-Based Indexing, Search, and Retrieval; Object and Face Recognition; Object Detection and Localization

In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, 191-197, 2014 , Lisbon, Portugal

Authors: Hao Wang ; Ya Zhang and Zhe Xu

Affiliation: Shanghai Jiao Tong University, China

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.

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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 (VISIGRAPP 2014) - Volume 1: VISAPP; ISBN 978-989-758-004-8; ISSN 2184-4321, SciTePress, 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 (VISIGRAPP 2014) - Volume 1: VISAPP},
year={2014},
pages={191-197},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004746801910197},
isbn={978-989-758-004-8},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2014) - Volume 1: VISAPP
TI - Exploring Residual and Spatial Consistency for Object Detection
SN - 978-989-758-004-8
IS - 2184-4321
AU - Wang, H.
AU - Zhang, Y.
AU - Xu, Z.
PY - 2014
SP - 191
EP - 197
DO - 10.5220/0004746801910197
PB - SciTePress