图像语义学的探索：我们在正确的灯柱下寻找吗？
In Quest of Image Semantics: Are We Looking for It Under the Right Lamppost?
摘要：
在过去的几年里，我们见证了一个戏剧性的增长的研究集中在语义图像理解。事实上，如果不了解图像内容，成功完成任何图像处理任务都是令人难以置信的。直到最近，这种理解的最终需求已经得到满足的知识，领域专家或视觉系统主管有助于每一个图像处理应用。互联网的出现彻底改变了这种状况。视觉信息的因特网源在整个Web上扩散和分散，因此现在必须将信息内容发现和评估的责任交给能够在远程图像位置处执行图像内容评估的图像理解代理（机器或计算机程序）。基于内容的图像检索（CBIR）技术的发展是朝着正确方向迈出的正确一步，大约在十年前推出。不幸的是，自那时以来进展甚微。其原因可以从CBIR设计人员继续坚持的长期误解中看出。我希望我的论点能帮助他们改变主意。
英文摘要：
In the last years we witness a dramatic growth of research focused on semantic image understanding. Indeed, without understanding image content successful accomplishment of any image-processing task is simply incredible. Up to the recent times, the ultimate need for such understanding has been met by the knowledge that a domain expert or a vision system supervisor have contributed to every image-processing application. The advent of the Internet has drastically changed this situation. Internet sources of visual information are diffused and dispersed over the whole Web, so the duty of information content discovery and evaluation must be relegated now to an image understanding agent (a machine or a computer program) capable to perform image content assessment at a remote image location. Development of Content Based Image Retrieval (CBIR) techniques was a right move in a right direction, launched about ten years ago. Unfortunately, very little progress has been made since then. The reason for this can be seen in a rank of long lasting misconceptions that CBIR designers are continuing to adhere to. I hope, my arguments will help them to change their minds.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
