# Planogram Compliance Control via Object Detection, Sequence Alignment, and Focused Iterative Search Source: [Planogram Compliance Control via Object Detection, Sequence Alignment, and Focused Iterative Search]() Collection index: [llms.txt]() Data updated: 2025-10-26T00:51:11.369Z Authors: M. Erkin Y\\"ucel, Cem \\"Unsalan Published: 2022-12-02T07:10:57.000Z ## Abstract Smart retail stores are becoming the fact of our lives. Several computer vision and sensor based systems are working together to achieve such a complex and automated operation. Besides, the retail sector already has several open and challenging problems which can be solved with the help of pattern recognition and computer vision methods. One important problem to be tackled is the planogram compliance control. In this study, we propose a novel method to solve it. The proposed method is based on object detection, planogram compliance control, and focused and iterative search steps. The object detection step is formed by local feature extraction and implicit shape model formation. The planogram compliance control step is formed by sequence alignment via the modified Needleman-Wunsch algorithm. The focused and iterative search step aims to improve the performance of the object detection and planogram compliance control steps. We tested all three steps on two different datasets. Based on these tests, we summarize the key findings as well as strengths and weaknesses of the proposed method. ## Recorded benchmark results A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. ## Original sources and implementation [Original paper]() [PDF]()