@inproceedings{ad2d160580644a349d50048fba81b76e,
title = "Saliency detection: A self-adaption sparse representation approach",
abstract = "Saliency detection is essential to visual attention modelling and various computer vision tasks. Representation and measurement are two important issues for saliency models. Good representation and reasonable measurement are both critical issues in modelling visual saliency mechanism. For every input image, we obtain a self-adaptive dictionary that describes the image content effectively and image prior that forces sparsity in every location in the image using the K-SVD algorithm. For saliency measurement, background firing rate (BFR) is defined for each sparse features and it is followed by feature activation rate (FAR) computation to measure the bottom-up visual saliency.",
keywords = "Background firing rate, Feature activation rate, K-svd algorithm, Saliency detection, Selfadaptive, Visual attention model",
author = "Gaoxiang Zhang and Feng Jiang and Debin Zhao and Xiaoshuai Sun and Shaohui Liu",
year = "2011",
doi = "10.1109/ICIG.2011.189",
language = "英语",
isbn = "9780769545417",
series = "Proceedings - 6th International Conference on Image and Graphics, ICIG 2011",
publisher = "IEEE Computer Society",
pages = "461--465",
booktitle = "Proceedings - 6th International Conference on Image and Graphics, ICIG 2011",
address = "美国",
note = "6th International Conference on Image and Graphics, ICIG 2011 ; Conference date: 12-08-2011 Through 15-08-2011",
}