Abstract
Current saliency detection methods mainly work on exploring the potential of low-level and high-level visual features, such as color, texture and face, but treat location information as a weak assistance or completely ignore it. In this paper, we reveal the importance of location information in saliency detection. We analyze the largest public image dataset for saliency detection THUS10000, and find the relationship between content location and saliency distribution. To further validate the effect of location information, we propose two location based saliency detection approaches, location based Gaussian distribution and location based saliency propagation, which make use of no or weak assistance of image content. Experimental results show that location based saliency detection can obtain much better performance than random selection, even better than most state-of-the-art saliency detection methods.
| Original language | English |
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| Title of host publication | ICIMCS 2014 - Proceedings of the 6th International Conference on Internet Multimedia Computing and Service |
| Publisher | Association for Computing Machinery |
| Pages | 10-13 |
| Number of pages | 4 |
| ISBN (Print) | 9781450328104 |
| DOIs | |
| Publication status | Published - 1 Jan 2014 |
| Event | 6th International Conference on Internet Multimedia Computing and Service, ICIMCS 2014 - Xiamen, China Duration: 10 Jul 2014 → 12 Jul 2014 |
Conference
| Conference | 6th International Conference on Internet Multimedia Computing and Service, ICIMCS 2014 |
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| Country/Territory | China |
| City | Xiamen |
| Period | 10/07/14 → 12/07/14 |
Keywords
- Location information
- Patch representation
- Saliency detection
- Saliency propagation
ASJC Scopus subject areas
- Human-Computer Interaction
- Computer Networks and Communications
- Computer Vision and Pattern Recognition
- Software