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题名:
Bottom-up attention based on C1 features of HMAX model
作者: Yu, Huapeng1,2,3; Xu, Zhiyong1; Fu, Chengyu1; Wang, Yafei2
出版日期: 2012
会议名称: Proceedings of SPIE: Optoelectronic Imaging and Multimedia Technology II
会议日期: 2012
DOI: 10.1117/12.999263
通讯作者: Yu, H. (musicfish1973@qq.com)
中文摘要: This paper presents a novel bottom-up attention model only based on C1 features of HMAX model, which is efficient and consistent. Although similar orientation-based features are commonly used by most bottom-up attention models, we adopt different activation and combination approaches to get the ultimate map. We compare the two different operations for activation and combination, i.e. MAX and SUM, and we argue they are often complementary. Then we argue that for a general object recognition system the traditional evaluation rule, which is the accordance with human fixations, is inappropriate. We suggest new evaluation rules and approaches for bottom-up attention models, which focus on information unloss rate and useful rate relative to the labeled attention area. We formally define unloss rate and useful rate, and find efficient algorithm to compute them from the original labeled and output attention area. Also we discard the commonly adopted center-surround assumption for bottom-up attention models. Comparing with GBVS based on the suggested evaluation rules and approaches on complex street scenes, we show excellent performance of our model. © Copyright SPIE.
英文摘要: This paper presents a novel bottom-up attention model only based on C1 features of HMAX model, which is efficient and consistent. Although similar orientation-based features are commonly used by most bottom-up attention models, we adopt different activation and combination approaches to get the ultimate map. We compare the two different operations for activation and combination, i.e. MAX and SUM, and we argue they are often complementary. Then we argue that for a general object recognition system the traditional evaluation rule, which is the accordance with human fixations, is inappropriate. We suggest new evaluation rules and approaches for bottom-up attention models, which focus on information unloss rate and useful rate relative to the labeled attention area. We formally define unloss rate and useful rate, and find efficient algorithm to compute them from the original labeled and output attention area. Also we discard the commonly adopted center-surround assumption for bottom-up attention models. Comparing with GBVS based on the suggested evaluation rules and approaches on complex street scenes, we show excellent performance of our model. © Copyright SPIE.
收录类别: Ei
语种: 英语
卷号: 8558
ISSN号: 0277786X
文章类型: 会议论文
页码: 85580W
Citation statistics:
内容类型: 会议论文
URI标识: http://ir.ioe.ac.cn/handle/181551/7698
Appears in Collections:光电探测与信号处理研究室(五室)_会议论文

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作者单位: 1. Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China
2. School of Optoelectronic Information, University of Electronic Science and Technology of China, Chengdu 610054, China
3. Graduate University, Chinese Academy of Sciences, Beijing 100039, China

Recommended Citation:
Yu, Huapeng,Xu, Zhiyong,Fu, Chengyu,et al. Bottom-up attention based on C1 features of HMAX model[C]. 见:Proceedings of SPIE: Optoelectronic Imaging and Multimedia Technology II. 2012.
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