Home Camera Appearance Discrimination Dataset

In the current retail e-commerce industry, the growing demand for security solutions has led to an increase in the variety of surveillance cameras. However, distinguishing between different types of cameras (spherical, gun-type, PTZ) remains a challenge due to the lack of comprehensive datasets. Existing solutions often struggle with accuracy, leading to misclassifications. This dataset aims to address these technical issues by providing high-quality labeled images for effective training of models in camera type discrimination. The data will be collected using high-resolution cameras in varied lighting conditions to ensure diversity. Quality control measures will include multi-round annotations, consistency checks, and expert reviews to ensure high labeling accuracy. The images will be stored in JPG format and organized by camera type for easy access.