Content-Based Interactive Emotional Image Retrieval
基于内容的交互式感性图象检索

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.