节点文献
基于概率图模型的图像整体场景理解综述
Survey on image holistic scene understanding based on probabilistic graphical model
【摘要】 近年来,计算机图像理解技术在智能交通、卫星遥感、机器视觉、医疗图像分析、网络图像搜索等多个领域得到广泛应用。图像整体场景理解作为其延伸,其复杂性和综合性远高于基本图像理解任务。针对这一特点,从图像理解基本框架、图像整体场景理解研究价值和意义、典型模型等多方面进行了归纳与分析,重点介绍了四种代表性的整体场景理解模型,并详细比较了模型架构。最后指出了目前图像整体场景理解研究不足以及未来发展方向,为该领域的进一步研究提供参考。
【Abstract】 In the recent years, the computer image understanding has wide and profound applications in intelligence traffic, satellite remote sensing, machine vision, image analysis of medical treatment, Internet image search and etc. As its extension, the image holistic scene understanding is more complex and integrated than basic image scene understanding task.In this paper, the basic framework for image understanding, the researching implication and value, typical models for image holistic scene understanding were summarized. The four typical holistic scene understanding models were introduced, and the model frameworks were thoroughly compared. At last, some research insufficiency and future direction in image holistic scene understanding were presented, which pointed out some new insights for the further research in this area.
【Key words】 image understanding; holistic scene understanding; probabilistic graphical model; cascaded classification model; Conditional Random Field(CRF);
- 【文献出处】 计算机应用 ,Journal of Computer Applications , 编辑部邮箱 ,2014年10期
- 【分类号】TP391.41
- 【被引频次】5
- 【下载频次】612