Logo detection

A system comprising:

• a processing device;
• and
• a non-transitory computer-readable medium communicatively coupled to the processing device, wherein the processing device is configured to execute program code stored in the non-transitory computer-readable medium and thereby perform operations comprising:
• receiving a source image at the processing device;
• detecting, in the source image and using a first logo detection model implemented by the processing devices, a candidate region for determining a logo in the source image;
• extracting, from the candidate region and by a neural network implemented using the processing device, a feature vector of the candidate region;
• determining, for each reference feature vector from a set of reference feature vectors stored in a database, a respective matching score between the reference feature vector and the feature vector of the candidate region, wherein each reference feature vector in the set of reference feature vectors is extracted from a respective image of a respective target logo in a set of target logos;
• selecting a first reference feature vector associated with a highest matching score among the set of reference feature vectors, the first reference feature vector extracted from a first image of a first target logo in the set of target logos;
• determining that the candidate region includes an image of the first target logo based on determining that the highest matching score is greater than a threshold value;
• receiving an image of a new target logo to be added to the set of target logos;
• extracting, using the neural network implemented using the processing device, a new reference feature vector from the image of the new target logo;
• and
• storing the new reference feature vector in the database.

A system comprising:

• means for receiving a source image;
• means for detecting, in the source image and using a first logo detection model, a candidate region for determining a logo in the source image;
• means for extracting, from the candidate region and using a neural network, a feature vector of the candidate region;
• means for determining, for each reference feature vector from a set of reference feature vectors stored in a database, a respective matching score between the reference feature vector and the feature vector of the candidate region, wherein each reference feature vector in the set of reference feature vectors is extracted from a respective image of a respective target logo in a set of target logos;
• means for selecting a first reference feature vector associated with a highest matching score among the set of reference feature vectors, the first reference feature vector extracted from a first image of a first target logo in the set of target logos;
• means for determining that the candidate region includes an image of the first target logo based on determining that the highest matching score is greater than a threshold value;
• means for receiving an image of a new target logo to be added to the set of target logos;
• means for extracting, using the neural network, a new reference feature vector from the image of the new target logo;
• and means for storing the new reference feature vector in the database.