Patent ID: 11961278
Assignee: BEIJING XIAOMI PINECONE ELECTRONICS CO., LTD.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 4:
5. A device for detecting an occluded image, comprising:
a processor; and
a memory configured to store instructions executable by the processor;
wherein the processor is configured to:
after an image is captured by a camera, obtain the image as an image to be detected;
input the image to be detected into a trained occluded-image detection model, wherein, the occluded-image detection model is trained based on original occluded images and non-occluded images by using a trained data feature augmentation network;
determine whether the image to be detected is an occluded image based on the occluded-image detection model; and
output an image detection result;
wherein the processor is configured to:
obtain the original occluded images and the non-occluded images;
train the data feature augmentation network based on the original occluded images; and
train the occluded-image detection model based on the original occluded images and the non-occluded images by using the trained data feature augmentation network;
wherein the processor is configured to:
generate a finger template image and a non-finger image based on each original occluded image, wherein the finger template image is obtained by removing an area not occluded by a finger from the original occluded image, and the non-finger image is obtained by removing an area occluded by the finger from the original occluded image; and
generate a plurality of training data sets, wherein each training data set comprises one finger template image, one non-finger image and one original occluded image, and a plurality of training data sets are used to train the data feature augmentation network in each round of training;
wherein the processor is configured to:
obtain mask data based on the original occluded image, the mask data indicating an occluded location in the original occluded image; and
generate the finger template image and the non-finger image based on the original occluded image and the mask data;
wherein the processor is configured to:
obtain a processed non-occluded image based on the mask data and the non-occluded image, wherein the processed non-occluded image is obtained by removing an area corresponding to the mask data from the non-occluded image;
input the finger template image and the processed non-occluded image into the trained data feature augmentation network to generate a generation feature of the non-occluded image;
input the original occluded image into a feature network to extract an original feature of the original occluded image, the occluded-image detection model comprising the feature network;
input the generation feature of the non-occluded image and the original feature of the original occluded image into a classification network for training, the occluded-image detection model comprising the classification network; and
determine that the training of the data feature augmentation network is finished when a loss function of the occluded-image detection model converges.