An electronic device includes a memory configured to store instructions, and a processor configured to execute the instructions to configure the processor to obtain a first heat map feature and a first coordinate value feature based on a face image, and detect a face key point based on the first heat map feature and the first coordinate value feature.

A method includes generating, based on user images, a user 3-D model. The method proceeds with obtaining, via a user interface, a request to graphically represent an accessory on to a user graphical representation. This user graphical representation is generated using the user 3-D model. In response to this request, an accessory 3-D model is obtained. Further, the method includes positioning, via the user interface and based on parameters of the user 3-D model and of the accessory 3-D model, an accessory graphical representation on to the user graphical representation. The method further includes updating, in response to detecting user movement, the user 3-D model and the accessory 3-D model and presenting, via the user interface and based on these updated 3-D models, the accessory graphical representation and the user graphical representation in accordance with the user movement.

A vehicle system includes a detection device structurally configured to capture an image, a door lock, where the door lock is positionable between a locked position and an unlocked position, a controller communicatively coupled to the detection device and the door lock, the controller including a processor and a non-transitory computer readable and executable instruction set, which when executed, causes the processor to receive a captured image of a user from the detection device, determine whether the captured image of includes protective equipment worn by the user, and direct the door lock to move into the unlocked position in response to determining that the protective equipment in the captured image meets a configurable protective equipment baseline.

A method for generating a final image from an initial image including an object suitable to be worn by an individual. The presence of the object in the initial image is detected. A first layer is superposed on the initial image. The first layer includes a mask at least partially covering the object in the initial image. The appearance of at least one part of the mask is modified. The suppression of all or part of an object in an image or a video is enabled. Also, a process of augmented reality intended to be used by an individual wearing a vision device on the face, and a try-on device for a virtual object.

A method and an associated device for detecting fraud during automatic face recognition, the method comprising the following steps: acquiring a first image of the face by means of a first sensor having a first field angle, and a second image of the face by means of a second sensor having a second field angle that is narrower than the first field angle; analyzing the first image to verify that there is no frame around the face; and analyzing the second image to verify that there is no moiré effect.

A system for quantifying viewer engagement with a video playing on a display includes at least one camera to acquire image data of a viewing area in front of the display. A microphone acquires audio data emitted by a speaker coupled to the display. The system also includes a memory to store processor-executable instructions and a processor. Upon execution of the processor-executable instructions, the processor receives the image data and the audio data and determines an identity of the video displayed on the display based on the audio data. The processor also estimates a first number of people present in the viewing area and a second number of people engaged with the video. The processor further quantifies the viewer engagement of the video based on the first number of people and the second number of people.

Systems, devices, media, and methods are presented for generating ideograms from a set of images received in an image stream. The systems and methods detect at least a portion of a face within the image and identify a set of facial landmarks within the portion of the face. The systems and methods determine one or more characteristics representing the portion of the face, in response to detecting the portion of the face. Based on the one or more characteristics and the set of facial landmarks, the systems and methods generate a representation of a face. The systems and methods position one or more graphical elements proximate to the graphical model of the face and generate an ideogram from the graphical model and the one or more graphical elements.

Methods and apparatus provide for: capturing an image of an object, which includes a face of a person wearing an optical display apparatus by which to observe a stereoscopic image that contains a first parallax image and a second parallax image obtained when the object in a three-dimensional (3D) space is viewed from different viewpoints; identifying the optical display apparatus included in the image of the object; and generating an image of the face of the person that does not include the optical display apparatus by excluding the identified optical display apparatus, and instead by adding features of the face of the person to a region in which the identified optical display apparatus is excluded.

Disclosed herein are a method and apparatus for active identification based on gaze path analysis. The method may include extracting the face image of a user, extracting the gaze path of the user based on the face image, verifying the identity of the user based on the gaze path, and determining whether the face image is authentic.

Methods and systems for training a neural network include generate an image of a mask. A copy of an image is generated from an original set of training data. The copy is altered to add the image of a mask to a face detected within the copy. An augmented set of training data is generated that includes the original set of training data and the altered copy. A neural network model is trained to recognize masked faces using the augmented set of training data.