799 results about "Posture recognition" patented technology

A gesture-based recognition system obtains a vehicle occupant's desired command inputs through recognition and interpretation of his gestures. An image of the vehicle's interior section is captured and the occupant's image is separated from the background, in the captured image. The separated image is analyzed and a gesture recognition processor interprets the occupant's gesture from the image. A command actuator renders the interpreted desired command to the occupant along with a confirmation message, before actuating the command. When the occupant confirms, the command actuator actuates the interpreted command. Further, an inference engine processor assesses the occupant's state of attentiveness and conveys signals to a drive assist system if the occupant in inattentive. The drive-assist system provides warning signals to the inattentive occupant if any potential threats are identified. Further, a driver recognition module readjusts a set of vehicle's personalization functions to pre-stored settings, on recognizing the driver.

The invention discloses a physical education assisting system and method based on human body posture recognition. The system comprises a depth shooting device, a standard action storage unit, a display terminal, an action comparison unit and a prompting device, wherein the depth shooting device is used for obtaining user action depth image sequences comprising movement action of a user following the demonstration action; the standard action storage unit is used for storing a standard action model and standard action demonstration image sequences corresponding to the standard action model; the display terminal is used for displaying the standard action demonstration image sequences for the user; the action comparison unit is used for comparing the user action depth image sequence at a scheduled time point or time period with the standard action model at the corresponding time point or the time period, and obtaining the difference between the user action and the standard action model; the prompting device is used for outputting action evaluation information or action correction prompting information to a display device according to the difference. According to the physical education assisting system and method, the user does not need to wear a special recognition device, the manufacturing cost of the system is lowered, and the user experience is improved.

Systems, articles, and methods perform gesture identification with limited computational resources. A wearable electromyography (“EMG”) device includes multiple EMG sensors, an on-board processor, and a non-transitory processor-readable memory that stores data and/or processor-executable instructions for performing gesture identification. The wearable EMG device detects and determines features of signals when a user performs a physical gesture, and processes the features by performing a decision tree analysis. The decision tree analysis invokes a decision tree stored in the memory, where storing and executing the decision tree may be managed by limited computational resources. The outcome of the decision tree analysis is a probability vector that assigns a respective probability score to each gesture in a gesture library. The accuracy of the gesture identification may be enhanced by performing multiple iterations of the decision tree analysis across multiple time windows of the EMG signal data and combining the resulting probability vectors.

The invention discloses a method and a device for reconstructing a three-dimensional face based on a single face image. The method comprises the following steps of: performing posture recognition on a face image by utilizing face structure priori knowledge, and estimating rotating direction and angle of a face plane by combining face measurement and projective geometry so as to set a rotating angle of the three-dimensional face; estimating the depth of two-dimensional characteristic points on the face image by adopting an artificial neural network, and acquiring three-dimensional coordinates of the characteristic points; converting a common three-dimensional face model into a specific model by adopting a Dirichlet free deformation algorithm; and mapping the three-dimensional face model by adopting characteristic points extracted from the two-dimensional image. Therefore, the true three-dimensional model is constructed through the single face image, the three-dimensional modeling accuracy is effectively improved, the three-dimensional modeling time is shortened and the three-dimensional modeling cost is reduced.

Disclosed are methods and systems for monitoring and correcting sitting posture of a user and for discouraging sedentary behavior. The system comprises a processor, a portable seat cover with embedded pressure sensors and an angle sensor, a notification device, and a non-transitory storage medium for storing program code. The program code, when executed by the processor, causes the processor to initiate an idleness timer to count how long the user has been sitting, monitor the user's sitting posture by receiving real-time sensor measurements; identify a sitting posture by applying a posture identification rule, generate a posture correction notification through the notification device if the identified sitting posture is not ergonomically correct, determine whether a sedentary threshold has been reached and generate a stand notification if the sedentary threshold has been reached. Embodiments of the present invention help improve sitting posture and reduce sedentary behavior to minimize associated adverse health effects.

The invention discloses a human body action recognition method based on a TP-STG framework, which comprises the following steps: taking video information as input, adding priori knowledge into an SVMclassifier, and providing a posteriori discrimination criterion to remove a non-personnel target; segmenting a personnel target through a target positioning and detection algorithm, outputting the personnel target in a target frame and coordinate information mode, and providing input data for human body key point detection; utilizing an improved posture recognition algorithm to carry out body partpositioning and correlation degree analysis so as to extract all human body key point information and form a key point sequence; a space-time graph is constructed on a key point sequence through an action recognition algorithm, the space-time graph is applied to multi-layer space-time graph convolution operation, action classification is carried out through a Softmax classifier, and human body action recognition in a complex scene is achieved. According to the method, the actual scene of the ocean platform is combined for the first time, and the provided TP-STG framework tries to identify worker activities on the offshore drilling platform for the first time by using methods of target detection, posture identification and space-time diagram convolution.

A posture recognition apparatus recognizes instructions signified by postures of persons present in the surroundings, from images obtained with an image capture device. The posture recognition apparatus includes an outline extraction device that extracts an outline of a body which is a candidate for a person from the images; a distance calculation device that calculates a distance to the body being the candidate, from distance information of each pixel within the outline in the image; a search device that searches for a candidate for a hand of a person based on the outline and the distance to the body represented by the outline; and a posture determination device that determines an instruction corresponding to the relative position of the candidate for a hand and the outline, and outputs this determination result as a posture determination result.

An example input system calculates a specified position on a screen of a display device, the position being specified by an operating device. The input system includes an attitude calculation section, an identification section, and a specified position calculation section. The attitude calculation section calculates an attitude of the operating device. The identification section identifies one of a plurality of display devices toward which the operating device is directed, based on the attitude of the operating device. The specified position calculation section calculates a specified position in accordance with the attitude of the operating device as a position on a screen of the display device identified by the identification section.

The invention relates to a mattress fitting human body curves and a height adjusting method of the mattress, and belongs to the technical field of home life articles. According to the height adjusting method, the headrest area height of the mattress can be adjusted, that is, the height adjusting method comprises the following steps: firstly, a sleeping posture recognition model is established based on statistical pattern recognition; secondly, obtained human body pressure data are input in the sleeping posture recognition model, and sleeping postures with the highest similarity are taken as an output result; finally, a controller controls the working state of a height adjusting device according to the output result of the sleeping posture recognition model, so as to ensure that the headrest area of the mattress can be adjusted up and down. The mattress provided by the invention has the advantages that not only can the pillow height requirements of different people be met, but also the different pillow height requirements of people lying on the side and on the back can be met; through appropriate height adjustment for a spondylopathy patient, recovery of the vertebral curve of the spondylopathy patient can be facilitated; for people always lowering or raising heads to work, spondylopathy can be prevented.

The invention provides a target object property recognition method and device and relates to the field of image recognition technology. The method is executed by the adoption of a recognition network.The recognition network comprises a feature extraction network, a pedestrian re-recognition network, a pedestrian posture recognition network and a pedestrian property recognition network, wherein the pedestrian re-recognition network, the pedestrian posture recognition network and the pedestrian property recognition network are connected with the feature extraction network, and parameters of therecognition network are obtained through joint training by the pedestrian re-recognition network, the pedestrian posture recognition network and the pedestrian property recognition network based on the mode of sharing the feature extraction network. The method comprises the steps that the feature extraction network extracts feature information of a target object; and the pedestrian property recognition network determines properties of the target object based on the feature information. Through the target object property recognition method and device, the pedestrian property recognition network can acquire richer and more comprehensive feature information by means of sharing the feature extraction network with the pedestrian re-recognition network and the pedestrian posture recognition network, and therefore the accuracy and robustness of property recognition are effectively improved.

The invention provides a pair of intelligent gloves, method and system for calorie consumption and hand posture recognition. The pair of intelligent gloves comprises a processor module, a memory module, a communication module, an induction module, an early warning prompt module, a display module, a power module, a switch module and a cloud server. The memory module, the communication module, the induction module, the early warning prompt module, the display module, the power module, the switch module and the cloud server are respectively connected with the processor module. The induction module comprises a pressure sensor and an IMU. The pressure sensor and the IMU are respectively used for being responsible for sensing hand stress strength and IMU data in users' fitness process, collecting source data according to user strength training and sending the source data to the processor module. The processor module is responsible for preprocessing of the source data. According to the pair of intelligent gloves, in the strength training process, the detection accuracy rate of detected motions is high, the rate of false alarm is low, and alarm signals can be sent when the hand posture is deviated.

A trailer target detection system includes a camera located on a vehicle and arranged to capture video images of a trailer towed by the vehicle. The system includes an image processor processing the video images to detect a gesture by a user indicative of position of target on the trailer and identifying location of the target based on the detected gesture. A vehicle trailer backup assist system includes a camera and an image processor for processing images to detect a gesture and determine a command based on the gesture. The processor controls backing of the trailer based on the command.

The invention discloses a face posture identification method based on rarefaction Bayesian regression in the image processing technique field, which comprises the following steps: extracting Gabor character for face posture image with Gabor filter; stacking the sampled character to one-dimensional vector after down sampling for Gabor character; acquiring the essential lower dimensional subspace of the face posture image and the corresponding projection matrix with the linear tangent space arrangement for the training sample; training the identification parameter with rarefaction Bayesian regression method in the lower dimensional subspace; mapping the projection matrix of every detecting sample to the lower dement ional subspace by training; proceeding the face posture identification with trained identification parameter. The invention can acquire the uncertain solution of the face posture, which reduces the wrong radio.

The invention discloses a shadow-boxing movement judging and guiding system based on kinect and a guiding method adopted by the shadow-boxing movement judging and guiding system. The system comprises a kinect depth sensor data acquisition module, a skeleton information filtration module, a feature information extraction module, a posture judgment module, a key posture correcting and guiding module and a consistency and standard judgment module for a group of movements. With the adoption of the system and the method, the judgment and guidance for the shadow-boxing movements are realized, and due to the design of the kinect depth sensor, the depth information is provided while the image information is provided, and therefore, the accuracy for the movement posture recognition is enhanced.

The invention relates to intelligent detection devices, and discloses an intelligent method and system for body building posture recognition, evaluation, early-warning and intensity estimation. The method comprises the steps that firstly, a thin film pressure sensor and an IMU on a pressure sensor on intelligent gloves are used for collecting original data generated in strength training; secondly, the original data is transmitted to a processor module for data preprocessing; thirdly, the processor module transmits pressure senor and IMU data obtained through preprocessing to an APP of a mobile terminal through a communication unit in a wireless communication mode. The intelligent method and system for body building posture recognition, evaluation, early-warning and intensity estimation have the advantages that the work of measuring calories and recognizing hand postures is carried out based on the existing sensor technology, an effective data processing method and an effective algorithm model are adopted, the method and the system can be widely applied to strength training, good and beneficial references are provided for body building fans, and recommendation for a dietary recipe and nutrition balancing in a later stage can be provided.

The invention discloses a target object posture recognition method, and the method comprises the steps: obtaining a current video frame; detecting a preset key point of the target object in the current video frame, and obtaining preset key point information of the target object in the current frame; according to the preset key point information, judging whether the position change of the preset key points of the current target object in the current frame and the previous f frames meets a first preset attitude condition, and/or judging whether the position relationship between the preset key points of the current target object in the current frame meets a second preset attitude condition; if the preset posture condition is met, the current target object posture is recognized as a preset posture, f is a preset natural number, and the preset posture condition is set according to the position characteristics between the key points of the to-be-recognized posture of the target object. According to the method of the invention, the method can accurately recognize the small change of the posture, is wide in application range, is low in requirements for an image in a video frame, is high inposture recognition accuracy, and is small in false detection and missing detection of posture recognition.

The invention discloses a human posture recognition method based on skeleton feature point extraction mainly to solve the problem on how to recognize human postures using a single camera. The method is implemented by the steps as follows: (1) inputting a video; (2) preprocessing the video; (3) extracting a coarse skeleton; (4) extracting skeleton feature points; (5) classifying the skeleton feature points; (6) performing gesture recognition; and (7) outputting a gesture recognition result. According to the invention, a coarse skeleton is acquired based on the shortest distance from the pixels of a profile graph to the edge, then, skeleton feature points are calculated and classified based on the distance from a chest node, and finally, a gesture is judged according to the relative position information of the skeleton feature points and the chest node. Human actions can be judged without a lot of calculation under the condition that there is only video steam input of a single camera. The human posture recognition method has the advantages of less calculation, low hardware requirement, high accuracy, and strong adaptability.

To include a focused ion beam apparatus fabricating a sliced specimen by processing a specimen as well as observing the sliced specimen, a scanning electron microscope observing the slice specimen, a gas-ion beam irradiation apparatus performing finishing processing by irradiating a gas-ion beam onto a surface of the sliced specimen, a specimen stage on which the sliced specimen is fixed and having at least one or more rotation axis, a specimen posture recognition means recognizing positional relation of the sliced specimen with respect to the specimen stage and a specimen stage control means controlling the specimen stage based on a specimen posture recognized by the posture recognition means and an installation angle of the gas-ion beam irradiation apparatus in order to allow an incident angle of the gas-ion beam with respect to the obverse or the reverse of the sliced specimen to be a desired value.