Salient Foreground Object Detection based on Sparse Reconstruction for Artificial Awareness
Jingyu Wang, Ke Zhang, Kurosh Madani, Christophe Sabourin, Jing Zhang
2015
Abstract
Artificial awareness is an interesting way of realizing artificial intelligent perception for machines. Since the foreground object can provide more useful information for perception and informative description of the environment than background regions, the informative saliency characteristics of the foreground object can be treated as a important cue of the objectness property. Thus, a sparse reconstruction error based detection approach is proposed in this paper. To be specific, the overcomplete dictionary is trained by using the image features derived from randomly selected background images, while the reconstruction error is computed in several scales to obtain better detection performance. Experiments on popular image dataset are conducted by applying the proposed approach, while comparison tests by using a state of the art visual saliency detection method are demonstrated as well. The experimental results have shown that the proposed approach is able to detect the foreground object which is distinct for awareness, and has better performance in detecting the information salient foreground object for artificial awareness than the state of the art visual saliency method.
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Paper Citation
in Harvard Style
Wang J., Zhang K., Madani K., Sabourin C. and Zhang J. (2015). Salient Foreground Object Detection based on Sparse Reconstruction for Artificial Awareness . In Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-989-758-123-6, pages 430-437. DOI: 10.5220/0005571204300437
in Bibtex Style
@conference{icinco15,
author={Jingyu Wang and Ke Zhang and Kurosh Madani and Christophe Sabourin and Jing Zhang},
title={Salient Foreground Object Detection based on Sparse Reconstruction for Artificial Awareness},
booktitle={Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2015},
pages={430-437},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005571204300437},
isbn={978-989-758-123-6},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - Salient Foreground Object Detection based on Sparse Reconstruction for Artificial Awareness
SN - 978-989-758-123-6
AU - Wang J.
AU - Zhang K.
AU - Madani K.
AU - Sabourin C.
AU - Zhang J.
PY - 2015
SP - 430
EP - 437
DO - 10.5220/0005571204300437