Edge flow

Morris, Gruff and Angelov, Plamen Parvanov (2015) Edge flow. In: Proceedings of the 2015 IEEE International Conference on Systems, Man, and Cybernetics (SMC) :. IEEE, pp. 1942-1948. ISBN 9781479986972

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In this paper we introduce a new data driven method to novelty detection and object definition in dynamic video streams that indiscriminately detects both static and moving objects in the scene. A sliding window density estimation is introduced in order to reliably detect texture edges. A Sobel filtering process is used to extract gradient of edges. Using this new approach, the detection of object textures1 can be done accurately and in real-time. In this paper we demonstrate the capabilities of the algorithm on video scenarios, and show that object textures in the scene are reliably detected. We are able to show clearly the capability of the algorithm to be robust in occlusion scenarios; working in real-time, and defining clear objects where other techniques attribute such small detections to noise.

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02 Mar 2016 14:22
Last Modified:
10 May 2024 02:16