Computer Vision for Supporting Image Search
This work targets the problem of improving image search for users, but it appears incremental as it builds on existing computer vision advancements without introducing new methods or data.
The paper addresses the underdeveloped application of direct image or video search by users, motivated by limitations in human memory, and outlines the requirements for computer vision to support this approach.
Computer vision and multimedia information processing have made extreme progress within the last decade and many tasks can be done with a level of accuracy as if done by humans, or better. This is because we leverage the benefits of huge amounts of data available for training, we have enormous computer processing available and we have seen the evolution of machine learning as a suite of techniques to process data and deliver accurate vision-based systems. What kind of applications do we use this processing for ? We use this in autonomous vehicle navigation or in security applications, searching CCTV for example, and in medical image analysis for healthcare diagnostics. One application which is not widespread is image or video search directly by users. In this paper we present the need for such image finding or re-finding by examining human memory and when it fails, thus motivating the need for a different approach to image search which is outlined, along with the requirements of computer vision to support it.