Planogram Compliance Checking Based on Detection of Recurring Patterns
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Abstract (arXiv)
In this paper, a novel method for automatic planogram compliance checking in retail chains is proposed without requiring product template images for training. Product layout is extracted from an input image by means of unsupervised recurring pattern detection and matched via graph matching with the expected product layout specified by a planogram to measure the level of compliance. A divide and conquer strategy is employed to improve the speed. Specifically, the input image is divided into several regions based on the planogram. Recurring patterns are detected in each region respectively and then merged together to estimate the product layout. Experimental results on real data have verified the efficacy of the proposed method. Compared with a template-based method, higher accuracies are achieved by the proposed method over a wide range of products.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Feb 2016.
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Citing papers per year: 2022: 2; 2023: 1; 2024: 1.
4 papers.
- 2022An Improved Deep Learning Approach For Product Recognition on Racks in Retail Storescited by 2
- 2022Planogram Compliance Control via Object Detection, Sequence Alignment, and Focused Iterative Searchcited by 1
- 2023Concept-based Anomaly Detection in Retail Stores for Automatic Correction using Mobile Robotscited by 0
- 2024Embedded Planogram Compliance Control Systemcited by 0
- 2024Embedded Planogram Compliance Control System12 Jan 2024
- 2023Concept-based Anomaly Detection in Retail Stores for Automatic Correction using Mobile Robots21 Oct 2023
- 2022Planogram Compliance Control via Object Detection, Sequence Alignment, and Focused Iterative Search2 Dec 2022
- 2022An Improved Deep Learning Approach For Product Recognition on Racks in Retail Stores26 Feb 2022