- 期刊
- OpenAccess
Visual Attention Region Determination Using Low-Level Features
並列摘要
In this study, a visual attention region determination approach using low-level luminance, color, and region features is proposed. First, the contrast map of an image is obtained by computing the contrast between each pixel and its ”thresholding” neighboring pixels in eight directions, based on the just noticeable difference (JND) model. Then, the block-based edge map and standard deviation representation are used to generate the region mask of the image. The saliency map of the image is generated by using the contrast map and the region mask of the image. Finally, based on the saliency map of the image, a visual attention region determination scheme is proposed to determine the visual attention regions in the image. Based on the experimental results obtained in this study, the performance of the proposed approach is better than that of three comparison approaches.
被引用紀錄
延伸閱讀
- You, C. B. (2015). Middle-level Feature Description for Human Action Recognition [master's thesis, National Chung Cheng University]. Airiti Library. https://www.airitilibrary.com/Article/Detail?DocID=U0033-2110201614032739
- 王佑鈞（2011）。Low Resolution Feature Evaluation and Appliance Recognition〔碩士論文，國立臺灣大學〕。華藝線上圖書館。https://doi.org/10.6342/NTU.2011.00465
- 王淑慧（2013）。The Value Orientation of Multi-Dimensional Evaluation。马来西亚人文与社会科学学报，2(1)，55-68。https://doi.org/10.6962/MJHSS.201306_2(1).0005
- Liu, C. Y. (2014). Sufficient Dimension Reduction with Extra Information [master's thesis, National Taiwan University]. Airiti Library. https://doi.org/10.6342/NTU.2014.01161
- 陳萬鴻（2011）。Video Caption Region Detection and Completion〔碩士論文，國立臺北科技大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0006-1808201113224600