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Salient object detection and classification for stereoscopic images

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Abstract

Stereoscopic images have become more and more prevalent following the rapid advances in 3D capturing and display techniques. However, there has been little research on visual content analysis for stereoscopic images. In this paper, we address the challenging problem of object detection and classification for stereoscopic images. An iterative method that can mutually boost salient object detection and object classification is proposed for stereoscopic images. This method includes two steps. In the first step, a 3D saliency detection method, which includes the contrastive and occlusion cues contained in each stereoscopic image pair along with the discriminative features provided by the SVM classifier, is proposed to localize object of interest in the stereoscopic images. In the second step, the bag of word features of foreground and background is pooled by using the localization information, and then is applied to train the SVM classifier. Each of the two steps benefits from the gradual improvement result in the other, no matter in the training or the testing process. To evaluate the performance of our approach, a 6-object class dataset of stereoscopic images real objects viewed under general lighting conditions, poses and viewpoints is set up. Our experimental results on the dataset, for object localization and object classification, demonstrate the effectiveness of the method.

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Notes

  1. http://photos.3dvisionlive.com/

  2. http://www.vlfeat.org/

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Acknowledgments

We would like to thanks the Flickr users and the NVIDIA 3D Vision Live sharers for their sharing photos. We also would like to thank Yuzhen Niu, Yujie Geng, Xueqing Li and Feng Liu for they providing the website links.

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Authors and Affiliations

  1. Department of Automation, University of Science and Technology of China, Hefei, Anhui, People’s Republic of China

    Kai Kang, Yang Cao, Jing Zhang & Zengfu Wang

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  1. Kai Kang
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Correspondence to Yang Cao.

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Kang, K., Cao, Y., Zhang, J. et al. Salient object detection and classification for stereoscopic images. Multimed Tools Appl 75, 1443–1457 (2016). https://doi.org/10.1007/s11042-014-2142-8

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  • DOI: https://doi.org/10.1007/s11042-014-2142-8

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