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Publication Type : Book Chapter
Publisher : Lecture Notes in Computational Vision and Biomechanics
Source : Lecture Notes in Computational Vision and Biomechanics, Springer Netherlands, Volume 28, p.399-411 (2018)
Campus : Coimbatore
School : School of Engineering
Department : Computer Science
Year : 2018
Abstract : Planogram are visual representations of a store’s products and services designed to help retailers ensure that the right merchandise is consistently on display, and that inventory is controlled at a level that guarantees that the right number of products are on each and every shelf. The main objective of this work is to propose an algorithm using image processing and machine learning as its base to find and detect the changes in the arrangement of objects present in the retail stores. The proposed algorithm is capable of identifying void space, count objects of similar type and thus helps in tracking the changes. Blob detection superseded by classification using a discriminative machine learning approach with the extracted statistical features of the objects has been used in this proposed algorithm. Experimental results are quite promising and hence this algorithm can be used to detect any changes occurring in a scene. © 2018, Springer International Publishing AG.
Cite this Research Publication : M. Muthugnanambika, Bagyammal T., Dr. Latha Parameswaran, and Vaiapury, K., “An automated vision based change detection method for planogram compliance in retail stores”, in Lecture Notes in Computational Vision and Biomechanics, vol. 28, Springer Netherlands, 2018, pp. 399-411.