Detection of Customer Interested Garments in Surveillance Video using Computer Vision
This addresses a domain-specific problem for retail analytics in India, but it is incremental as it adapts existing methods to a new dataset.
The paper tackles the problem of detecting customer interest in garments from surveillance video, specifically for Indian clothing, and reports achieving high precision and recall on a dataset of CCTV footage from a garments store.
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.