Some embodiments are directed to a biometric authentication system including headwear having a plurality of biosensors each configured to sample muscle activity so as to obtain a respective time-varying signal, a data store for storing a data set representing characteristic muscle activity for one or more users, and a processor configured to process the time-varying signals from the biosensors in dependence on the stored data set so as to determine a correspondence between a time-varying signal and characteristic muscle activity of one of the one or more users, and in dependence on the determined correspondence, authenticate the time-varying signals as being associated with that user.

Technology described herein includes a method that includes obtaining a set of color-coded sequences, each of which includes a sequence of colors. Each color-coded sequence has auto-correlation properties characterized by a merit factor larger than a first predetermined threshold, and cross-correlation properties among the color-coded sequences characterized by a demerit factor lower than a second predetermined threshold. A color-coded sequence is randomly selected from the set of color-coded sequences. A subject is illuminated in accordance with the sequence of colors in the selected color-coded sequence. A sequence of images of the subject are captured, and are temporally synchronized with illumination by the color-coded sequence. A filtered response image is generated from the sequence of images by a matched filtering process. Based on the filtered response image, it is determined that the subject is an alternative representation of a live person. In response, access to a secure system is prevented.

Systems and methods are disclosed. A digitized human vocal expression of a user and digital images are received over a network from a remote device. The digitized human vocal expression is processed to determine characteristics of the human vocal expression, including: pitch, volume, rapidity, a magnitude spectrum identify, and/or pauses in speech. Digital images are received and processed to detect characteristics of the user face, including detecting if any of the following is present: a sagging lip, a crooked smile, uneven eyebrows, and/or facial droop. Using the human vocal expression characteristics and face characteristics, a determination is made as to what action is to be taken. A cepstrum pitch may be determined using an inverse Fourier transform of a logarithm of a spectrum of a human vocal expression signal. The volume may be determined using peak heights in a power spectrum of the human vocal expression.

Provided are systems and methods for portrait animation. An example method includes receiving, by a computing device, a scenario video, where the scenario video includes information concerning a first face, receiving, by the computing device, a target image, where the target image includes a second face, determining, by the computing device and based on the target image and the information concerning the first face, two-dimensional (2D) deformations of the second face in the target image, and applying, by the computing device, the 2D deformations to the target image to obtain at least one output frame of an output video.

A system and method of processing media for facial manipulation. Input frames are downscaled to a lower resolution and facial detection identifies a target face in each input frame. The location of the target face is determined in the downscaled frames and the locations are projected to the input frames based on the pixel differences between the frames. Facial landmark detection is then performed on a cropped image from the original input frame. The facial landmarks are used to adjust the orientation of the input frames so that the target face in each input frame is in a standard orientation. Facial landmark detection is again performed on the target face in each frame while in the standard orientation to produce more accurate landmarks. Facial manipulation can then be executed based on the landmarks in the aligned input images. The orientation of the images with the manipulated faces are then reverted.

An image forming apparatus includes: an imaging device that captures a reference facial image used for determining a change in a facial expression, and a user facial image; a processor that determines an emotion in the user facial image based on an amount of the change in the facial expression from the reference facial image, and performs message support corresponding to the emotion in the user facial image; and a user interface that detects an input operation by a user without delay in setting a printing condition when a print job is executed in response to a request made by the user. The processor obtains the reference facial image captured by the imaging device at a time point when the user interface detects the input operation without delay and the facial expression is assumed to be a reference for the change in the facial expression.

An electronic device for face recognition is provided. The electronic device is used to exclude an ineligible object to be identified according to the relative relationship between object distances and image sizes, the image variation with time and/or the feature difference between images captured by different cameras to prevent the possibility of cracking the face recognition by using a photo or a video.

A display device includes a display configured to output image data, and a controller configured to extract a contour noise removal region from the image data, acquire motion information of the image data, and remove contour noise based on a de-contour gain value corresponding to the motion information.

A method and a system for measuring a feature of persons. The method includes defining the feature of persons being measured. The method further includes measuring values of data points from a sample of digital images comprising the persons, according to the defined feature by a first algorithm. The method further includes generating a distribution curve of the measured values. The method further includes standardizing the measured values by implementing a hyperbolic tangent function transformation.

A method for calibrating an animation includes obtaining a static source image of a source face; capturing, by an image capturing device, a driving video of a human; determining whether a driving face, of the human, is present in each of the video frames; measuring a driving face position and a driving face size in a calibration reference frame of the driving video; generating each of one or more modified video frames based on the calibration reference frame and each of one or more subsequent video frames; and outputting, for each of the driving video frames, the source image in response to determining that the driving face is not present, and outputting the source image and the modified video frame in response to determining that the driving face is present.