Provided is an object recognition method which includes obtaining a first visible-light image acquired by the first camera device and a second visible-light image acquired by the second camera device; performing exposure processing on the first visible-light image according to the luminance information of the bright area image of the first visible-light image and performing exposure processing on the second visible-light image according to the luminance information of the dark area images of the first visible-light image and/or the second visible-light image, where the dark area image is an area image having a luminance value less than or equal to the preset value; and performing target object detection on the first visible-light image obtained after exposure processing and the second visible-light image obtained after exposure processing and recognizing and verifying a target object according to the detection result.

A determination system includes: a projection control unit that controls a projection unit to project a random marker within an angle of view of an imaging unit; an acquisition unit that obtains an image of a target person including the marker from the imaging unit; and a determination unit that determines whether or not the target person imaged by the imaging unit is a living body on the basis of a state of the marker included in the image. According to such a determination system, it is possible to accurately determine whether or not the target person is a living body. Therefore, for example, it is possible to avoid a breakthrough of biometric authentication by an illegal method, or the like.

Disclosed is a face verification method and apparatus. The method including analyzing a current frame of a verification image, determining a current frame state score of the verification image indicating whether the current frame is in a state predetermined as being appropriate for verification, determining whether the current frame state score satisfies a predetermined validity condition, and selectively, based on a result of the determining of whether the current frame state score satisfies the predetermined validity condition, extracting a feature from the current frame and performing verification by comparing a determined similarity between the extracted feature and a registered feature to a set verification threshold.

Image processing systems and methods are provided for authorizing the performance at a computer terminal of an age-restricted activity. An estimated human age is determined based on human characteristics of a structure detected in an image captured at the computer terminal. It is determined whether the structure exhibits at least one liveness characteristic indicating the human characteristics from which the estimated human age is determined have been captured directly from a living human at the computer terminal. A positive determination is made as to whether performance of the age-restricted activity is authorized if the estimated human age meets a predetermined age requirement and the structure is determined to exhibit at least one liveness characteristic, and a negative determination is made if: i) the estimated human age does not meet the predetermined age requirement; and/or ii) the structure is not determined to exhibit at least one liveness characteristic.

Face recognition systems are vulnerable to the presentation of spoofed faces, which may be presented to face recognition systems, for example, by an unauthorized user seeking to gain access to a protected resource. A face liveness detection method that addresses this vulnerability utilizes motion analysis to compare the relative movement among three regions of interest in a facial image and based upon that comparison to make a face liveness determination.

Biometrics are increasingly used to provide authentication and/or verification of a user in many security and financial applications for example. However, “spoof attacks” through presentation of biometric artefacts that are “false” allow attackers to fool these biometric verification systems. Accordingly, it would be beneficial to further differentiate the acquired biometric characteristics into feature spaces relating to live and non-living biometrics to prevent non-living biometric credentials triggering biometric verification. The inventors have established a variety of “liveness” detection methodologies which can block either low complexity spoofs or more advanced spoofs. Such techniques may provide for monitoring of responses to challenges discretely or in combination with additional aspects such as the timing of user's responses, depth detection within acquired images, comparison of other images from other cameras with database data etc.

The technology described in this document can be embodied in a method for preventing access to a secure system based on determining a captured image to be of an alternative representation of a live person. The method includes capturing an image of a subject illuminated by an infrared (IR) illumination source, and extracting, from the image, a portion representative of an iris of the subject. The method also includes determining that an amount of high-frequency features in the portion of the image satisfies a threshold condition indicative of the image being of an alternative representation of a live person, and in response, identifying the subject in the image to be an alternative representation of a live person. Responsive to identifying the subject in the image to be an alternative representation of a live person, the method further includes preventing access to the secure system.

The present invention discloses system and method for fake face identification. The system is a multi-spectral sensing based bio-security system. The system uses CNN module along with thermal sensors to detect human face and also detects the human temperature. The system authenticates a human face and in case of temperature generates an alarm as an alert.

Facial recognition-based authentication comprises obtaining a first image of a target object, updating projection information associated with a display by a display device, obtaining a second image of the target object, the second image being an image of the target object after the projection information is updated, obtaining an image difference data based at least in part on the first image and the second image, and determining whether the target object is a virtual object based at least in part on the image difference data.

Exemplary embodiments of this disclosure provide a living body detection method and apparatus, an electronic device, a storage medium, and a payment system, a video surveillance system, and an access system to which the living body detection method is applied, and generally belong to the field of biometric recognition technologies. The living body detection method can include obtaining an image of a to-be-detected object performing key point detection on a biometric feature corresponding to the to-be-detected object in the image, and constructing a constraint box in the image according to detected key points. Further, the method can include capturing a shape change of the constraint box constructed in the image, and determining the to-be-detected object as a prosthesis in response to capturing an abnormal deformation of the constraint box or detecting no key points.