Abstract: A method and system for integrated liveness detection and identity verification initiates a verification process via an application in a device having a front camera and a rear camera, activates both front and rear cameras, records a video stream of an identification document from the rear camera simultaneously with a video stream of the face of the user from the front camera, synchronizes video frames from the both video streams, analyzes the video frames and detects liveness of the user and liveness of the identification document. The rear camera stream is analyzed to capture and to extract a face image from the identification document and to recognize the identification document. The front camera stream is analyzed to capture a live image of the face of the user. The live image of the face of the user is compared with the face image. Confirmation of the user's identity is made.

Abstract: The present application relates to the field of computer software technologies, and in particular, to a face spoofing attack detection method and system. The suggested method comprises capturing an image; determining a context of the captured image; highlighting a part of the captured image to generate an image with the highlighted part, wherein the highlighted part is a potential spoofing region determined based on the context of the captured image; combining the captured image with the image with the highlighted part to generate a summarized image; performing face spoofing attack detection in the summarized image, wherein only the highlighted part has priority in the face spoofing attack detection, generating a general spoofing score as a result of the face spoofing attack detection; comparing the general spoofing score result with a threshold for face liveness detection.

Abstract: The present application relates to the field of computer software technologies, and in particular, to a face spoofing attack detection method and system. The suggested method comprises capturing an image containing a face of a user; highlighting at least one part of the captured image, which is a potential spoofing region; selecting a method for user liveness detection for a specific highlighted at least one part of the captured image, which is a potential spoofing region; performing user liveness detection using the selected method and based on the highlighted at least one part of the captured image to obtain a general liveness score; and comparing the general liveness score result with a threshold for face spoofing attack detection.

Abstract: Disclosed herein are an around view provision apparatus and a vehicle including the same. The around view provision apparatus includes a plurality of cameras mounted on a vehicle, a display, and a processor configured to receive a plurality of images from the plurality of cameras, to check locations of the images using first area patterns in the plurality of images, to compensate a parameter in an image using second area patterns located in overlapping areas between the plurality of images, and to generate an around view image based on the compensated parameter. Accordingly, it is possible to provide an accurate around view image based on a calibrated image.

Abstract: Disclosed herein are an around view provision apparatus and a vehicle including the same. The around view provision apparatus includes a plurality of cameras mounted on a vehicle, a display, and a processor configured to receive a plurality of images from the plurality of cameras, to check locations of the images using first area patterns in the plurality of images, to compensate a parameter in an image using second area patterns located in overlapping areas between the plurality of images, and to generate an around view image based on the compensated parameter. Accordingly, it is possible to provide an accurate around view image based on a calibrated image.