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The Point Pair Feature (Drost et al. 2010) has been one of the mostsuccessful 6D pose estimation method among model-based approaches as anefficient, integrated and compromise alternative to the traditional local andglobal pipelines. During the last years, several variations of the algorithmhave been proposed. Among these extensions, the solution introduced byHinterstoisser et al. (2016) is a major contribution. This work presents avariation of this PPF method applied to the SIXD Challenge datasets presentedat the 3rd International Workshop on Recovering 6D Object Pose held at the ICCV2017. We report an average recall of 0.77 for all datasets and overall recallof 0.82, 0.67, 0.85, 0.37, 0.97 and 0.96 for hinterstoisser, tless, tudlight,rutgers, tejani and doumanoglou datasets, respectively.

6D Pose Estimation using an Improved Method based on Point Pair Features