A knowledge-based approach in video frame processing using Iterative Qualitative Data Analysis

Abstract

The ability to acquire, identify and represent the knowledge that a human expert has about a particular domain is a powerful key method in the development of a knowledge-based computer system. This paper demonstrates a methodology for acquiring and analyzing data based on semi-structured interview responses conducted upon human experts. Human experts are asked to determine the acceptability of an image containing person(s) in a sequence of images. Different experts may have different judgments and collectively the image values or attributes from their subjective judgment may contribute to the main factors of consideration in determining the overall image acceptability. The aim of this paper is to identify the most appropriate image attributes used by human experts during an image selection task which is in line with our research objectives. We discuss the knowledge acquisition task by adopting the Iterative Qualitative Data Analysis (IQDA) approach and represent the knowledge into a set of filtering attributes.