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This paper presents a framework designed for the multi-object detectionpurposes and adjusted for the application of product search on the marketshelves. The framework uses a single feedback loop and a pattern resizingmechanism to demonstrate the top effectiveness of the state-of-the-art localfeatures. A high detection rate with a low false detection chance can beachieved with use of only one pattern per object and no manual parametersadjustments. The method incorporates well known local features and a basicmatching process to create a reliable voting space. Further steps comprise ofmetric transformations, graphical vote space representation, two-phase voteaggregation process and a cascade of verifying filters.

A framework for robust object multi-detection with a vote aggregation and a cascade filtering