A sensing device includes a substrate, a first circuit, a second circuit, a first photodetector, and a second photodetector. The substrate has a sensing region. The first circuit is disposed on the substrate and in the sensing region, and configured to sense a fingerprint. The second circuit is disposed on the substrate and in the sensing region, and configured to sense a living body. The first photodetector is electrically connected to the first circuit. The second photodetector is electrically connected to the second circuit. The area of the second photodetector is larger than the area of the first photodetector.

The present disclosure relates to a method performed in a fingerprint analysis system for facilitating differentiating between a live finger and a spoof finger. The method comprises acquiring a plurality of time-sequences of images, each of the time-sequences showing a respective finger as it engages a detection surface of a fingerprint sensor. Each of the time-sequences comprises at least a first image and a last image showing a fingerprint topography of the finger, wherein the respective fingers of some of the time-sequences are known to be live fingers and the respective fingers of some other of the time-sequences are known to be spoof fingers. The method also comprises training a machine learning algorithm on the plurality of time-sequences to produce a model of the machine learning algorithm for differentiating between a live finger and a spoof finger.

A system for authenticating a user attempting to access a computing device or a software application executing thereon. A data storage device stores one or more digital images or frames of video of face(s) of authorized user(s) of the device. The system subsequently receives from a first video camera one or more digital images or frames of video of a face of the user attempting to access the device and compares the image of the face of the user attempting to access the device with the stored image of the face of the authorized user of the device. To ensure the received video of the face of the user attempting to access the device is a real-time video of that user, and not a forgery, the system further receives a first photoplethysmogram (PPG) obtained from a first body part (e.g., a face) of the user attempting to access the device, receives a second PPG obtained from a second body part (e.g., a fingertip) of the user attempting to access the device, and compares the first PPG with the second PPG. The system authenticates the user attempting to access the device based on a successful comparison of (e.g., correlation between, consistency of) the first PPG and the second PPG and based on a successful comparison of the image of the face of the user attempting to access the device with the stored image of the face of the authorized user of the device.

A face liveness detection method is provided, and includes: receiving an image transmitted by a terminal, the image including a face of an object; performing data augmentation on the image, to obtain an extended image corresponding to the image, a number of extended images corresponding to the image being more than one; performing liveness detection on the extended images corresponding to the image, to obtain intermediate detection results of the extended images, a liveness detection model used in liveness detection being obtained by performing model training on an initial neural network model according to a sample image and extended sample images corresponding to the sample image; and obtaining a liveness detection result of the object in the image after fusing the intermediate detection results of the extended images.

Biometric identification methods and apparatuses (including devices and systems) for uniquely identifying one an individual based on wearable garments including a plurality of sensors, including but not limited to sensors having multiple sensing modalities (e.g., movement, respiratory movements, heart rate, ECG, EEG, etc.).

The invention presents a process for determining a video as being a spoof or a genuine recording of a live biometric characteristic, characterized in that it comprises the steps of: preprocessing (200) the video, determining a liveness score (300) of the video, said determination comprising, for each frame of a plurality of frames (j) of the video: computing a difference between a motion intensity of a current frame and that of each frame of a set of preceding frames to infer a differential motion intensity of the current frame, inferring (330), from the differential motion intensities of the plurality of frames, a motion intensity of the video, comparing (340) said motion intensity to a predetermined threshold, and assigning a liveness score to the video, and determining (400) whether the video is a genuine recording of a biometric characteristic or a spoof.

An electronic device for performing iris authentication, according to various examples of the present invention, can comprise: an image sensor for outputting an image obtained by photographing an eye part; a display for displaying an iris authentication screen image; and a control unit detecting at least a partial region from the captured eye part image so as to perform iris authentication by adjusting display characteristics of the display on the basis of a result obtained by comparing the size of the detected region with the size of a region required for the iris authentication, and various examples are possible.

Methods, systems, and computer-readable storage media for determining that a subject is a live person include capturing a set of images of a subject instructed to perform a facial expression. A region of interest for the facial expression is determined in a first image of the set, the first image representing a first facial state that includes the facial expression. A set of facial features is identified in the region of interest, the facial features being indicative of interaction between facial muscles and skin of the subject due to the subject performing the facial expression. A determination is made, based on the facial features, that the first image substantially matches a template image of the facial expression of the subject. Responsive to determining that the first image substantially matches the template image, identifying the subject as a live person.

In general, one innovative aspect of the subject matter described in this specification can be embodied in a computer-implemented method. The method includes, detecting, by an imaging device, the presence of an object to be imaged. The method further includes, measuring, by the imaging device, a first characteristic of the object to be imaged, and measuring, by the imaging device, a second characteristic of the object to be imaged. The method further includes, determining, by a computing device, that at least one of the first characteristic of the object or the second characteristic of the object exceeds a threshold; and in response to determining, indicating, by the computing device, whether the object to be imaged is one of a spoofed object or an actual object.

A processor-implemented vehicle controlling method includes: determining whether an object in a vehicle is a living object based on radio detection and ranging (radar) information received from a radar sensor; in response to a determination that the object is a living object, determining bioinformation of the object based on the radar information; and adjusting a temperature in the vehicle based on the bioinformation and temperature information received from a temperature sensor.