电脑软件和硬件的不断发展,使美术设计师的思维灵感方便地变成可视图像。丰富多采的电子图像库,有效地支持设计师在创作空间中飞翔。作品“未来计划”中,象征远古的山脉,古代文明的金字塔,现代文明的摩天大楼,在设计师的艺术空间中并肩...电脑软件和硬件的不断发展,使美术设计师的思维灵感方便地变成可视图像。丰富多采的电子图像库,有效地支持设计师在创作空间中飞翔。作品“未来计划”中,象征远古的山脉,古代文明的金字塔,现代文明的摩天大楼,在设计师的艺术空间中并肩而立,地球的演变和人类文明的进程浓缩在方寸之间。一块飞升的大陆,载负着地球现代科技,在人类期盼的目光中,去迎接远方来宾,在即将召开的圆桌会议上,共同编修未来计作品仅应用了Photoshop和Corel图像库,在短时间中完成构思、设计和制作。 Follow me please,让我们一起开始制作过程。展开更多
This paper presents a new method for refining image annotation by integrating probabilistic la- tent semantic analysis （PLSA） with conditional random field （CRF）. First a PLSA model with asymmetric modalities is c...This paper presents a new method for refining image annotation by integrating probabilistic la- tent semantic analysis （PLSA） with conditional random field （CRF）. First a PLSA model with asymmetric modalities is constructed to predict a candidate set of annotations with confidence scores, and then model semantic relationship among the candidate annotations by leveraging conditional ran- dom field. In CRF, the confidence scores generated lay the PLSA model and the Fliekr distance be- tween pairwise candidate annotations are considered as local evidences and contextual potentials re- spectively. The novelty of our method mainly lies in two aspects ： exploiting PLSA to predict a candi- date set of annotations with confidence scores as well as CRF to further explore the semantic context among candidate annotations for precise image annotation. To demonstrate the effectiveness of the method proposed in this paper, an experiment is conducted on the standard Corel dataset and its re- sults are ＇compared favorably with several state-of-the-art approaches.展开更多
文摘电脑软件和硬件的不断发展,使美术设计师的思维灵感方便地变成可视图像。丰富多采的电子图像库,有效地支持设计师在创作空间中飞翔。作品“未来计划”中,象征远古的山脉,古代文明的金字塔,现代文明的摩天大楼,在设计师的艺术空间中并肩而立,地球的演变和人类文明的进程浓缩在方寸之间。一块飞升的大陆,载负着地球现代科技,在人类期盼的目光中,去迎接远方来宾,在即将召开的圆桌会议上,共同编修未来计作品仅应用了Photoshop和Corel图像库,在短时间中完成构思、设计和制作。 Follow me please,让我们一起开始制作过程。
基金Supported by the National Basic Research Priorities Programme(No.2013CB329502)the National High Technology Research and Development Programme of China(No.2012AA011003)+1 种基金the Natural Science Basic Research Plan in Shanxi Province of China(No.2014JQ2-6036)the Science and Technology R&D Program of Baoji City(No.203020013,2013R2-2)
文摘This paper presents a new method for refining image annotation by integrating probabilistic la- tent semantic analysis （PLSA） with conditional random field （CRF）. First a PLSA model with asymmetric modalities is constructed to predict a candidate set of annotations with confidence scores, and then model semantic relationship among the candidate annotations by leveraging conditional ran- dom field. In CRF, the confidence scores generated lay the PLSA model and the Fliekr distance be- tween pairwise candidate annotations are considered as local evidences and contextual potentials re- spectively. The novelty of our method mainly lies in two aspects ： exploiting PLSA to predict a candi- date set of annotations with confidence scores as well as CRF to further explore the semantic context among candidate annotations for precise image annotation. To demonstrate the effectiveness of the method proposed in this paper, an experiment is conducted on the standard Corel dataset and its re- sults are ＇compared favorably with several state-of-the-art approaches.
