Liveness test method and apparatus

A processor implemented liveness test method, the liveness test method comprising:

• extracting an interest region of an object from a portion of the object in an input image;
• performing a liveness test on the object using a neural network model-based liveness test model, the liveness test model using image information of the interest region as provided first input image information to the liveness test model and determining liveness based at least on extracted texture information from the image information of the interest region by the liveness test model;
• and
• indicating a result of the liveness test,
• wherein the liveness test model uses image information of the input image or image information of the portion of the object in the input image as provided second input image information to the liveness test model that is also provided the first input image information,
• wherein the determining of the liveness is based at least on the extracted texture information from the first input image information and spatial information extracted based on the second input image information by the liveness test model, and
• wherein an effective resolution of the first input image information is higher than an effective resolution of the second input image information.

Aliveness test computing apparatus comprising:

• at least one processor configured to:
• extract an interest region of an object from a portion of the object in an input image;
• perform a liveness test on the object using the neural network model-based liveness test model for each of one or more images of the object respectively input to the liveness test model,
• wherein image information of the interest region is provided, as first input image information, to a first input layer of the liveness test model,
• wherein image information of the input image or image information of the portion of the object is provided, as second input image information, to a second input layer of the liveness test model, and
• wherein for the performing of the liveness test, the at least one processor is further configured to determine, by the liveness test model, liveness of the object based at least on extracted texture information from the first input image information by the liveness test model and information extracted from the second input image information by the liveness test model;
• and
• provide a reference value indicating a result of the liveness determination.

A liveness test computing apparatus comprising:

• at least one processor configured to:
• extract an interest region of an object within a detected face region in an input image;
• perform a liveness test on the object using a convolutional neural network by providing a first input layer of the convolutional neural network image information of the interest region as first input image information, providing a second input layer of the convolutional neural network second input image information corresponding to the detected face region, and determining liveness based on a combination of first results dependent on texture information extracted from the image information of the interest region through a first convolutional layer of the convolutional neural network and second results dependent on spatial information extracted from the second input image information through a second convolutional layer of the convolutional neural network independent of the first convolutional layer;
• and
• selectively control access to other functions of the liveness test computing apparatus based on results of the performed liveness test.