614 results about "Head posture" patented technology

A gaze direction determining system and method is provided. A two-camera system may detect the face from a fixed, wide-angle camera, estimates a rough location for the eye region using an eye detector based on topographic features, and directs another active pan-tilt-zoom camera to focus in on this eye region. A eye gaze estimation approach employs point-of-regard (PoG) tracking on a large viewing screen. To allow for greater head pose freedom, a calibration approach is provided to find the 3D eyeball location, eyeball radius, and fovea position. Both the iris center and iris contour points are mapped to the eyeball sphere (creating a 3D iris disk) to get the optical axis; then the fovea rotated accordingly and the final, visual axis gaze direction computed.

The invention provides a system and a method for control through identifying user posture by an image extraction device, in which a hand posture, a head posture and variation of facial expression of the user are synchronously matched to form different combined postures so as to control an electronic device, and each combined posture can transmit a corresponding control instruction. Since the complexity of the combined postures is higher than that of inertia actions of people, the system and the method for control through identifying the user posture by the image extraction device can avoid unnecessary control instructions generated by unaware inertia actions of users.

A face horizontal direction measuring unit measures the angle of the face horizontal direction for a face image obtained by an imaging unit. By using information on the radius of the head and information on the shoulder position of the person obtained by the aforementioned measurement, a face vertical displacement measuring unit measures a face displacement in the vertical direction not affected by a head posture. According to the obtained displacement, the face angle in the vertical direction is decided. By using the obtained face direction, the angle of the gaze in the horizontal direction and the eyeball radius are measured. Further, a gaze vertical displacement measuring unit is provided for which measuring the pupil center position against the eyeball center position as the gaze displacement in the vertical direction. This displacement amount is used to measure the gaze angle in the vertical direction.

The invention discloses a user posture monitoring method and wearable equipment. The method comprises the following steps: setting an inertia sensor in the wearable equipment which is located at a user head when worn; when a user wears the wearable equipment, monitoring motion data of the user head through the inertia sensor in real time; performing posture calculation on the motion data to obtain posture data of the user head; determining whether a user head posture is correct according to the posture data and a preset strategy; and when the user head posture is incorrect, reminding the user. According to the scheme, the wearable equipment is located at the user head; the inertia sensor arranged in the wearable equipment and the user head can be kept relatively static, so that the motion data of the user head can be accurately monitored, and credible posture data of the user head can be acquired; by analysis of the credible posture data, effective monitoring of the user head posture is realized; and when the posture is incorrect, a warning can be sent to remind the user to pay attention to the health of the cervical vertebra.

The invention provides equipment and a method for detecting a head posture. The equipment for detecting the head posture comprises a multi-visual-angle image acquiring unit, a front human face image estimation unit, a head posture estimation unit and a coordinate conversion unit, wherein the multi-visual-angle image acquiring unit is used for acquiring visual angle images, which is shot from different angles, of an object; the front human face image estimation unit detects a visual angle image of a human face having a minimum yaw angle from the acquired visual angle images; the head posture estimation unit acquires a three-dimensional coordinate of a predetermined human face characteristic point from a human face three-dimensional model, detects the predetermined human face characteristic point and a two-dimensional coordinate of the predetermined human face characteristic point from the detected visual angle image, and calculates a first head posture relative to image capturing equipment for shooting the visual angle image of the human face having the minimum yaw angle according to the two-dimensional coordinate and the three-dimensional coordinate of the predetermined human face characteristic point; and the coordinate conversion unit converts the first head posture into a second head posture represented by a world coordinate system according to the world coordinate system coordinates of the image capturing equipment.

A virtual or augmented reality display system that controls a display using control information included with the virtual or augmented reality imagery that is intended to be shown on the display. The control information can be used to specify one of multiple possible display depth planes. The control information can also specify pixel shifts within a given depth plane or between depth planes. The system can also enhance head pose measurements from a sensor by using gain factors which vary based upon the user's head pose position within a physiological range of movement.

A system and a method are provided for generating a control instruction by using an image pickup device to recognize a user's posture. An electronic device is controlled according to different composite postures. Each composite posture is a combination of the hand posture, the head posture and the facial expression change of the user. Each composite posture indicates a corresponding control instruction. Since the composite posture is more complex than peoples' habitual actions, the possibility of causing erroneous control instruction from unintentional habitual actions of the user will be minimized or eliminated.

A method for tracking the location of the tip of the nose with a video camera, and a hands-free computer input device based thereon have been described. According to this invention, a convex shape such as the shape of the tip of the nose, is a robust object suitable for precise and smooth location tracking purposes. The disclosed method and apparatus are substantially invariant to changes in head pose, user preferred seating distances and brightness of the lighting conditions. The location of the nose can be tracked with pixel and sub-pixel accuracy.

The invention discloses a data driving face expression synthesis method based on Laplace transformation, comprising the following steps of: resolving face motion data captured after the face motion of a performer is acquired into a face expression motion and a head rigid motion; calculating the Laplace coordinates of each peak in a loaded neutral target face model; moving the face expression motion to the neutral target face model to make the neutral target face model have consistent expressions with the performer; and moving the head rigid motion to the target face model having the consistent expressions with the performer to make the final target face model have consistent face expressions and head postures with the performer. Based on a Laplace transformation technology being capable of keeping the original detail features of the model, the invention keeps the existing detail features on the target face model while realizing the moving of the face expressions, has the advantages of definite arithmetic, friendly interface and robust result and can be conveniently applied to the computer game field, the online chat field and other man-machine interaction fields.

The invention relates to a robust continuous emotion tracking method based on deep learning. The method comprises the steps that (1) a training sample is constructed, and a normalization model and a continuous emotion tracking model are trained; (2) an expression image is acquired and preprocessed, the expression image obtained after being preprocessed is sent to the trained normalization model, and an expression picture with standard illumination and a standard head posture is obtained; (3) a standard image obtained after normalization is used as input of the continuous emotion tracking model, expression-related features are automatically extracted and input through the continuous emotion tracking model, and a tracking result of a current frame is generated according to time sequence information; and the steps (2) and (3) are repeated till a whole continuous emotion tracking process is completed. The method based on deep learning is adopted to construct an emotion recognition model so as to realize continuous emotion tracking and prediction, the method has robustness on illumination and posture changes, and the time sequence information of expressions can be fully utilized to track the emotion of a current user more stably based on historical emotion features.

The invention provides a gesture recognition system and method adopting action segmentation and relates to the field of machine vision and man-machine interaction.The gesture recognition method comprises the following steps that firstly, head movements are detected, and head posture changes are calculated; then, a segmentation signal is sent according to posture estimation information, gesture segmentation beginning and end points are judged, if the signal indicates initiative gesture action segmentation, gesture video frame sequences are captured within a time interval of gesture execution, and preprocessing and characteristic extraction are conducted on gesture frame images; if the signal indicates automatic action segmentation, the video frame sequences are acquired in real time, segmentation points are automatically analyzed by analyzing the movement change rule of adjacent gestures for action segmentation, then vision-unrelated characteristics are extracted from segmented effective element gesture sequences, and a type result is obtained by adopting a gesture recognition algorithm for eliminating spatial and temporal disparities.The gesture recognition method greatly reduces redundant information of continuous gestures and the calculation expenditures of the recognition algorithm and improves the gesture recognition accuracy and real-timeliness.

The invention provides a head posture sensing device and a head posture sensing method. The device comprises an inertia sensor detection unit, an analogue-to-digital conversion unit connected with the inertia sensor detection unit and an information processing unit connected with the analogue-to-digital conversion unit, wherein the information processing unit is connected with an input unit and an output unit; the inertia sensor detection unit comprises an inertia sensor, and is used for detecting head posture information, and outputting an analogue signal of the head posture information; and the analogue-to-digital conversion unit comprises an analogue-to-digital converter, and is used for converting the analogue signal detected by the inertia sensor into a digital signal of the head posture information. According to the head posture sensing device and the head posture sensing method, various motion statuses of a head can be detected stably and efficiently, and motion parameters of the head can be acquired.

The invention provides a method, a device, a storage medium and a terminal device for detecting a line-of-sight point, wherein, the method comprises the following steps: obtaining a face image when anobserver looks at a display screen; extracting feature points of a face region and an eye region from the face image; tracking an initial picture sequence of the face image, iteratively calculating afeature point of the face region to obtain a head posture of the observer; determining a line-of-sight angle and a line-of-sight confidence parameter of the observer according to a characteristic point of the eye region; according to the head posture, the line-of-sight angle and the line-of-sight confidence parameter, and the distance of the observer to the display screen, determining the line-of-sight of the observer to be at a point-of-arrival position of the display screen. By adopting the invention, the position of the line of sight falling point of the observer can be conveniently, quickly and accurately determined.

The invention discloses a multidimensional sense man-machine interaction system and a multidimensional sense man-machine interaction method, which are based on combine interaction modes of head posture control, voice control, keyboard and mouse operation, etc. The system is composed of the following 8 modules: a user information collecting module, a user information identifying and analyzing module, a head posture control functional module, a voice control functional module, a storage module, an interface interaction module, a self-customizing module and a program control module. The method is realized by the following four processes: collecting user information, identifying and analyzing the user information, realizing head posture control or voice control and outputting a user interface. The system and the method disclosed by the invention have the advantages of large application range, good maintainability, good expandability and the like. In addition, the system provides a novel man-machine interaction process method for a computer user, so that the operation efficiency of a common user can be improved, and great help on neck fitness and learning of old people on computers can be realized.

The invention discloses a multi-index fusion-based driver fatigue detection method. The method comprises the steps of firstly, acquiring a face image of a driver in a normal state to carry out human face positioning, selecting a first face feature point, and determining a driver eye fatigue judgment threshold value through the first face feature point; acquiring a face image of the driver in a driving state, carrying out human face positioning, selecting a second face feature point, and calculating an eye fatigue index, a mouth fatigue index and a head posture fatigue index of the driver; andin combination with the eye fatigue index, the mouth fatigue index and the head posture fatigue index, judging whether the driver is in fatigue driving or not. According to the method, various physiological characteristics of a person in a fatigue state are comprehensively considered, and the fatigue state of the driver is detected in a multi-index fusion mode, so that the fatigue state of the driver can be detected more accurately, and the problems of easy disturbance and low identification accuracy of a traditional single-index detection method are effectively solved.

Improvements are provided to effectively assess a user's face and head pose such that a computer or like device can track the user's attention towards a display device(s). Then the region of the display or graphical user interface that the user is turned towards can be automatically selected without requiring the user to provide further inputs. A frontal face detector is applied to detect the user's frontal face and then key facial points such as left/right eye center, left/right mouth corner, nose tip, etc., are detected by component detectors. The system then tracks the user's head by an image tracker and determines yaw, tilt and roll angle and other pose information of the user's head through a coarse to fine process according to key facial points and/or confidence outputs by pose estimator.

A method for determining and measuring profile and frontal head posture and front views thereof to establish a 3-D model of a patient's head and face. In the method, a patient places his or her head in a natural head position and establishes a postural sagittal plane. Additionally, the practitioner may move the patients head to a corrected sagittal plane. If still necessary, an anatomic sagittal plane that comprises an anatomical midline of the patient's face when viewed from a frontal view is constructed. An profile anatomical coronal plane is located and aligned with the frontal anatomical sagittal plane. Next, an anatomical transverse plane is established through the soft tissue nasion and aligning it perpendicularly to the anatomical sagittal and coronal planes. By developing the 3 planes a 3-D reference frame is established from which soft tissue and hard tissue landmarks are identified and measured.

The invention discloses a synthetic video generation method based on three-dimensional face reconstruction and video key frame optimization. The synthetic video generation method comprises the following steps: optimizing and fitting each parameter of a three-dimensional face deformation model for an input face image by adopting a convolutional neural network; training a voice-to-expression and head posture mapping network by using the parameters of the target video and the face model, and acquiring facial expression and head posture parameters from the input audio by using the trained voice-to-expression and head posture mapping network; synthesizing a human face and rendering the synthesized human face to generate a vivid human face video frame; training a rendering network based on a generative adversarial network by using the parameterized face image and the face image in the video frame, wherein the rendering network is used for generating a background for each frame of face image; and performing face background rendering and video synthesis based on video key frame optimization. The background transition of each frame of the output synthesized face video is natural and vivid, and the usability and practicability of the synthesized face video can be greatly enhanced.