In Quest of Image Semantics: Are We Looking for It Under the Right Lamppost?
Abstract
Description
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.
In 2006, this paper has been submitted to 13 computer vision conferences, and was strongly rejected by 12 of them
In 2006, this paper has been submitted to 13 computer vision conferences, and was strongly rejected by 12 of them