The dataset for a vision-based unmanned kiosk

In recent years, many unmanned retail stores have been introduced with the development
of computer vision, sensors and wireless technology. However, the trend has slowed due to the costs
associated with implementation. A vision-based kiosk, which is only equipped with a vision sensor, can
be a compact and affordable option. The vision-based kiosk detects a product via CNN-based object
detectors and performs instance-level classification by aggregating detections from multiple cameras.
There are many public datasets for retail object recognition. However, the products that appear in the dataset are captured under certain conditions, such as a white background, on the shelf, and a pack shot. We provide a dataset which is constructed solely for the vision-based unmanned kiosk. The dataset consists of 115k images collected with the prototype unmanned kiosk system. In the system, multiple cameras are installed to capture an object from various viewpoints. For the actual purchasing process, retail products are selected and returned by customers in the scene