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Detection of Customer Interested Garments in Surveillance Video using Computer Vision

arXiv 2503.00442 ↗First posted 1 Mar 2025cs.CVcited by 0

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Abstract (arXiv)

One of the basic requirements of humans is clothing and this approach aims to identify the garments selected by customer during shopping, from surveillance video. The existing approaches to detect garments were developed on western wear using datasets of western clothing. They do not address Indian garments due to the increased complexity. In this work, we propose a computer vision based framework to address this problem through video surveillance. The proposed framework uses the Mixture of Gaussians background subtraction algorithm to identify the foreground present in a video frame. The visual information present in this foreground is analysed using computer vision techniques such as image segmentation to detect the various garments, the customer is interested in. The framework was tested on a dataset, that comprises of CCTV videos from a garments store. When presented with raw surveillance footage, the proposed framework demonstrated its effectiveness in detecting the interest of customer in choosing their garments by achieving a high precision and recall.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 3 of its 16 references that are in the map. First posted on arXiv 1 Mar 2025.

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References · 3

  1. 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,852
  2. 2019Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regressioncited by 1,368
  3. 2014Fashion Apparel Detection: The Role of Deep Convolutional Neural Network and Pose-dependent Priorscited by 3

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