Method and apparatus for checkout based on image identification technique of convolutional neural network

A checkout apparatus based on an image identification technique of convolutional neural network, comprising:

• an acquisition device for acquiring a plurality of pictures of a single item to be classified placed on a checkout counter, the plurality of pictures corresponding to a plurality of shooting angles one to one;
• an object detection device for performing object detection in each of the pictures to obtain a rectangular area image, the rectangular area image being an image corresponding to a rectangular area containing the item;
• a first classification device for obtaining a plurality of primary classification results correspondingly, according to a plurality of the rectangular area images and a pre-trained first-level classification model, and obtain a first-level classification result of the plurality of pictures according to the plurality of primary classification results and a pre-trained first-level linear regression model, the first-level classification model being a model that is constructed by the image identification technique of convolutional neural network and trained by all the items in the shopping place;
• a confirmation device for using the first-level classification result as a first classification result;
• and
• a checkout device for performing checkout according to the first classification result.

A checkout apparatus based on an image identification technique of convolutional neural network, comprising:

• cameras configured to acquire a plurality of pictures of a single item to be classified placed on a checkout counter, the plurality of pictures corresponding to a plurality of shooting angles one to one;
• a processor;
• and
• a memory configured to record processor-executable instructions, the processor configured to
• perform object detection in each of the pictures to obtain a rectangular area image that is an image corresponding to a rectangular area containing the item,
• obtain a plurality of primary classification results correspondingly, according to a plurality of the rectangular area images and a pre-trained first-level classification model, obtain a first-level classification result of the plurality of pictures according to the plurality of primary classification results and a pre-trained first-level linear regression model,
• use the first-level classification result as a first classification result, and perform checkout according to the first classification result,
• the first-level classification model being a model that is constructed by the image identification technique of convolutional neural network and trained by all the items in the shopping place.