用计算机视觉从监控视频中识别顾客试穿的服装
Detection of Customer Interested Garments in Surveillance Video using Computer Vision
- 基于高斯混合模型提取前景，结合图像分割识别服装
- 在服装店监控数据集上实现高精度与高召回率
- 专为复杂印度服饰设计，填补现有方法空白
人类基本需求之一是穿着衣物，本文旨在通过计算机视觉技术从监控视频中识别顾客购物时挑选的服装。现有方法多基于西方服饰数据集开发，难以处理印度服饰因结构复杂带来的挑战。本文提出一种基于视频监控的计算机视觉框架：首先使用高斯混合模型背景差分法提取视频帧中的前景区域，再利用图像分割等技术分析前景中的视觉信息，识别顾客感兴趣的服装。该框架在包含商场闭路电视视频的数据集上进行了测试，面对原始监控画面，能有效检测顾客对服装的兴趣，实现高精度与高召回率。
原文摘要 · Abstract (English)
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.
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