CSSE Seminar Series (CSSESS)

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The harmony search algorithm was developed in 2001 as a heuristic optimisation algorithm for use in diverse optimisation problems. After its introduction it was extensively used in multiple engineering disciplines with great success. In order to demonstrate the value of harmony search in computer vision applications I developed four novel algorithms based on harmony search that efficiently solves three problems that are commonly found in computer vision, namely visual tracking, visual correspondence matching and binary image restoration. Computer vision is a large discipline that includes solving many different kinds of optimisation problems. Many of these optimisation problems are discontinuous with derivative information difficult or impossible to come by. The most common solution is to use population based statistical optimisation algorithms like the particle filter, genetic algorithms, PSO, etc., but harmony search has never been investigated as a possible alternative. This is surprising since harmony search has been shown to be superior to these methods in several other engineering disciplines. I therefore aim to introduce harmony search to the computer vision researcher as a valuable optimisation tool through the introduction of three novel algorithms.

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