30 results about "Facial tracking" patented technology

Herein described is a system and method that tracks the face of a person engaged in a videophone conversation. In addition to performing facial tracking, the invention provides stabilization of facial images that are transmitted during the videophone conversation. The face is tracked by employing one or more algorithms that correlate videophone captured facial images against a stored facial image. The face may be better identified by way of employing one or more voice recognition algorithms. The one or more voice recognition algorithms may correlate utterances of the person engaged in a conversation to one or more stored utterances. The identified utterances are subsequently mapped to a stored facial image. In a representative embodiment, the system used for performing facial tracking and image stabilization comprises an image sensor, a lens, an actuator, and a controller / processor.

Method of applying virtual makeup and producing makeover effects to 3D face model driven by facial tracking in real-time includes the steps: capturing static or live facial images of a user; performing facial tracking of facial image, and obtaining tracking points on captured facial image; and producing makeover effects according to tracking points in real time. Virtual makeup can be applied using virtual makeup input tool such as a user's finger sliding over touch panel screen, mouse cursor or an object passing through makeup-allowed area. Makeup-allowed area for producing makeover effects is defined by extracting feature points from facial tracking points and dividing makeup-allowed area into segments and layers; and defining and storing parameters of makeup-allowed area. Virtual visual effects including color series, alpha blending, and / or superposition are capable of being applied. Makeover effect takes into account of lighting condition, facial posture rotation, face size scaling, and face translation, respectively.

A facial tracking method can include receiving a first vector of a first frame, and second vectors of second frames that are prior to the first frame in a video. The first vector is formed by coordinates of first facial feature points in the first frame and determined based on a facial registration method. Each second vector is formed by coordinates of second facial feature points in the respective second frame and previously determined based on the facial tracking method. A second vector of the first frame is determined according to a fitting function based on the second vectors of the first set of second frames. The fitting function has a set of coefficients that are determined by solving a problem of minimizing a function formulated based on a difference between the second vector and the first vector of the current frame, and a square sum of the coefficients.

A method of 3D morphing driven by facial tracking is provided. First, a 3D model is loaded. After that, facial feature control points and boundary control points are picked up respectively. A configure file “A.config” including the facial feature control points and boundary control points data that are picked up corresponding to the 3D avatar is saved. Facial tracking algorithm is started, and then “A.config” is loaded. After that, controlled morphing of a 3D avatar by facial tracking based on “A.config” is performed in real time by a deformation method having control points. Meanwhile, teeth and tongue tracking of the real-time face image, and scaling, translation and rotation of the real-time 3D avatar image is also provided. In addition, a control point reassignment and reconfiguration method, and a pupil movement detection method is also provided in the method of 3D morphing driven by facial tracking.

A facial tracking method for detecting and tracking at least one face image in a region during a time period. The facial tracking method includes a step of performing an image acquiring operation, a step of performing a facial detecting operation to detect whether there is any face image in the entire of a current photo image, and at least one step of performing a facial tracking operation. For performing the facial tracking operation, plural tracking frames are located around a face image of the current photo image, and a similarity between the face image of the current photo image and the image included in each tracking frame in order to judge whether the face image exists in the next photo image. By the facial tracking method of the present invention, the time period of tracking face images is largely reduced.

A head mounted display (HMD) in a VR system includes sensors for tracking the eyes and face of a user wearing the HMD. The VR system records calibration attributes such as landmarks of the face of the user. Light sources illuminate portions of the user's face covered by the HMD. In conjunction, facial sensors capture facial data. The VR system analyzes the facial data to determine the orientation of planar sections of the illuminated portions of face. The VR system aggregates planar sections of the face and maps the planar sections to landmarks of the face to generate a facial animation of the user, which can also include eye orientation information. The facial animation is represented as a virtual avatar and presented to the user. A facial tracking system generates a virtual rendering of a portion of a face of a user wearing a head-mounted display (HMD). The facial tracking system illuminates portions of the face inside the HMD. The facial tracking system captures a plurality of facial data of the portion of the face using one or more facial sensors located inside the HMD. A plurality of planar sections of the portion of the face are identified based at least in part on the plurality of facial data. The plurality of planar sections are mapped to one or more landmarks of the face. Facial animation information is generated based at least in part on the mapping, the facial animation information describing a portion of a virtual face corresponding to the portion of the user's face.

The present invention provides a target tracking method and device. The method includes: detecting a moving target from a captured video stream, wherein the video stream includes each video image; searching for a human face from the video image corresponding to the detected moving target Image; obtain the face tracking feature corresponding to each face image found, wherein the face tracking feature includes: face image features, distance between the face and the camera, and the duration of the face in the video image; According to the face tracking features of each face image, a tracking target is determined from each found face image; and the tracking target is tracked. Through the object tracking method and device provided in the present application, the camera can actively track the person to be photographed in the video, and improve the video shooting quality of the camera.

An emotional enhancement system for music and film that uses audio and video input to select or generate a stimulation pattern which stimulates the user's face using lights and electrical stimulation directed to certain points on the user's face and head which are believed to induce certain emotions. Using the system, a user's emotional experience of the music or film can be enhanced by inducing emotions in the user coordinated with portions of the music or film. In some embodiments, biometric sensors or cameras and facial tracking software may be used to monitor the emotions displayed by a user while listening to music or watching films, and adjust the stimulation accordingly.

Method for automatically measuring pupillary distance includes extracting facial features of face image, a head current center indicator is shown / displayed based on facial feature extraction, elliptical frame and target center indicator are shown, a first distance between head current center indicator and target center indicator is calculated to see if below a threshold range, then allowing head current center indicator, elliptical frame and target center indicator to disappear. Card window based on facial tracking result is shown. Credit card band detection is performed to see if located within card window. Card window then disappear. Elliptical frame of moving head and target elliptical frame are shown. Elliptical frame of the moving head is aligned with the target elliptical frame and maintaining a correct head posture. If elliptical frame of moving head is aligned with target elliptical frame, then allow them to disappear from view, and performing a pupillary distance measurement.

The embodiment of the present invention discloses an image acquisition method, device, device, and storage medium. The method includes: acquiring a user's image acquisition instruction; acquiring the user's gaze information through a face tracking device, wherein the gaze information includes gaze points and / or gaze direction; according to the gaze information, determine the position and / or direction of image acquisition to perform image acquisition. The technical solution of the embodiment of the present invention realizes real-time adjustment of the photographing position of the photographing camera according to the user's demand, thereby improving the flexibility of focusing of the camera in the device, and obtaining photographed images meeting the user's demand.

A facial tracking method can include receiving a first vector of a first frame, and second vectors of second frames that are prior to the first frame in a video. The first vector is formed by coordinates of first facial feature points in the first frame and determined based on a facial registration method. Each second vector is formed by coordinates of second facial feature points in the respective second frame and previously determined based on the facial tracking method. A second vector of the first frame is determined according to a fitting function based on the second vectors of the first set of second frames. The fitting function has a set of coefficients that are determined by solving a problem of minimizing a function formulated based on a difference between the second vector and the first vector of the current frame, and a square sum of the coefficients.