基于内容的交互式感性图象检索

Content-Based Interactive Emotional Image Retrieval

随着信息化社会的到来及信息高速公路计划的实施 ,人们越来越多地接触到大量的图象信息 ,因此基于内容的图象检索已经成为当前的一个热门研究课题 ,并在多媒体数据库、电子图书馆、商标管理、医疗图象管理、公安系统、卫星图象管理等方面得到广泛应用 .然而 ,大多数基于内容的图象检索系统主要是通过图象多维物理特征的相似性匹配来进行查询 ,而对于用户的爱好、情感等主观或感性化的因素则考虑较少 .为了弥补这方面的不足 ,提出了一种基于内容的交互式感性图象检索方法 .该方法采用交互式进化算法 ,并通过人机交互的方式 ,来将用户的直觉、情感等感性化的因素融入到进化过程 ,以便进行图象的交互式在线检索 ;针对在检索过程中 ,因进化的时间可能较长和因需要用户确定的适应度值较多而产生的用户疲劳问题 ,采用神经网络离线学习的方法来减轻用户疲劳 ,从而实现了根据用户的情感和基于图象内容的图象检索 ,并取得了较好的实验结果 .

With increased computing power, electronic storage capacity, and the rapid development of the Internet, the potential for large digital image libraries is now growing at an astonishing pace. Providing efficient access to images, however, is not an easy task. To overcome this difficulty, content-based image retrieval(CBIR) was thus proposed as a solution. In CBIR, images would be indexed by their own visual content, instead of being manually annotated by text-based keyword s. In this framework, many research studies have been performed, and many commercial and academic CBIR systems, widely applied in multimedia databases, digital libraries, medical image management, public security department and satellite image management, have been developed in the past few years. Most CBIR systems, however, answer users' query by similarity match based on multi-dimensional physical image features. Because of human subjectivity, different persons or the same person under different circumstances may perceive the same visual content differently. To address the difficulties arising from human subjectivity, we propose a content-based interactive emotional image retrieval approach. Through interactive evolution computation, human intuition and emotion is integrated into the evolution process to realize on-line retrieval by human-computer interaction. To deal with the problem that the user may tend to be tired arising from that the user has to evaluate a large number of individuals when the evolution time is too long, neural networks are used for off-line learning to alleviate human fatigue. Based on image content, an emotional image retrieval system has been realized. The experimental results demonstrate the effectiveness of our approach.