17 results about "Movement tracking" patented technology

Embodiments described herein relate to systems, devices, and methods for use in the implementation of a brain-computer interface that integrates real-time eye-movement tracking with brain activity tracking to present and update a user interface that is strategically designed for high speed and accuracy of human—machine interaction. Embodiments described herein also relate to the implementation of a hardware agnostic brain-computer interface with specific user interface adaptations to enable high-speed, intuitive, and accurate user manipulation of applications and / or machines.

A moving body tracking device obtains the position of a tracking object 55, and generates a signal for permitting irradiation of a target 50 with radiation when it is determined that the tracking object 55 exists inside a gate range. In the moving body tracking device, the gate range varies between timing when the tracking object 55 enters the inside from the outside of the gate range and timing when the tracking object exits from the inside to the outside. Accordingly, provided are a moving body tracking device and a radiation irradiation system with which it is possible to suppress a change in the dose distribution and a decrease in irradiation efficiency due to the influence of latency.

An apparatus for configuring a wearable device for exercise tracking includes a data storage unit for storing sensor data generated by a sensor arrangement in the wearable device based on sensed movement of the wearable device and optical movement data including representations of an individual obtained from an image-based monitoring system; and a processing unit configured to: execute a movement tracker model on the sensor data to determine a first exercise activity and an associated first confidence indicator; execute an optical tracker model on the optical movement data to determine a second exercise activity and an associated second confidence indicator; process the movement tracker model based on the first confidence indicator and the second confidence indicator.

The application provides a kind of park lane line perception method and system based on multi-source data fusion and prior map constraint, it is related to map and positioning navigation technical field, this method includes: collecting multi-source data and pre-processing image;Extract color, edge and semantic feature for weighted fusion, generate candidate lane line heat map;Obtain high-precision map prior information and project to image coordinate system, spatial screening is carried out to candidate point;Adaptive model fitting is carried out to effective point set, and lane line observation value is obtained;Kalman filtering tracking and prediction are carried out in combination with vehicle kinematic model;Comprehensive multi-dimensional index calculates confidence and carries out hierarchical processing.The application improves the detection robustness in complex environment by multi-feature fusion, uses map prior to carry out flexible constraint to eliminate noise, introduces motion tracking to ensure continuity when shielding, and realizes abnormal response through confidence evaluation, effectively solves the perception problem caused by unclear park lane line feature and variable environment.

Parallel processing computer systems and methods for real-time multimodal behavioral classification and dynamic content adaptation are provided. A parallel processing pipeline implements concurrent execution of sensor data ingestion, neural network inference, content adaptation, and rendering stages across specialized processor resources including graphics processing units and tensor processing units. The parallel processing pipeline achieves end-to-end latency of less than 200 milliseconds from sensor data capture to rendered content output, representing a reduction of at least 60% compared to conventional sequential architectures exhibiting latencies exceeding 500 milliseconds. A trained neural network model comprising feature extraction modules with parallel convolutional branches, a bidirectional Long Short-Term Memory temporal processing module, and a classification module processes multimodal sensor data including video frame data, audio waveform data, motion tracking data, and physiological sensor data to classify behavioral states and calculate engagement levels. A dynamic adjustment algorithm modifies content parameters including difficulty level, environmental complexity, and reinforcement schedule based on real-time performance metrics to maintain user performance within target ranges.

This invention provides a method for online force assessment of characters in a virtual reality environment, aiming to achieve real-time quantitative assessment, physical accuracy, and high robustness of force on humanoid character movements in virtual reality environments. This method combines a motion generation model and a physics optimizer, using an end-to-end integrated approach to dynamically estimate key mechanical parameters such as joint torque and ground reaction force. Specific steps include: acquiring user motion trajectory data from sparse sensors (such as VR headsets and controllers); generating preliminary full-body motion postures using a motion generation model based on discrete latent space learning; performing physical correction and force estimation on the motion using a physics optimization module (employing a dual proportional-differential controller and a motion tracking optimizer); integrating motion data and force parameters; and outputting character animation and force visualization results in real time through a rendering engine. Through the collaborative design of motion generation and physical force assessment, this invention significantly improves the realism, real-time performance, and adaptability of virtual character movements, making it suitable for VR applications such as security monitoring, medical training, and sports simulation, enhancing immersion and interaction efficiency.

The programmable weight movement tracking device may overcome the limitations of conventional fitness movement tracking devices. The device may function as an auxiliary unit that can be used in conjunction with any cable machine. An ideal device would combine the portability of fitness tracking devices with ease of operation and programming, all while maintaining a high degree of precision and versatility in a wide range of applications and devices. The device may comprise an array of optical sensors that allow for the precise tracking of particular movements. The device may further comprise a plurality of components to improve the precision and functionality of the device such as, for example, a top, mid-body, and bottom profile structure, a controller unit, a bottom base, a plurality of sensor units, a universal serial bus (USB) receiver, and / or an outer case.

Systems and methods for welding asset movement tracking are disclosed. In some examples, a welding asset tracking system may comprise an asset tracking network of tags, hubs, and / or gateways retained by welding assets within a welding area. Directions of travel of monitored assets may be determined by comparing the order in which assets are identified by the asset tracking network. The travel directions, travel paths, and / or ingress and egress of tracked assets from welding areas are stored for subsequent analysis and / or retrieval. Additionally or alternatively, functionality of tracked assets may be disabled and / or enabled based on whether the assets are authorized to be removed from a designated area.

This invention discloses a method for implementing AR (Augmented Reality) in urban underground pipe networks, relating to the field of pipe network AR technology. The method includes an underground pipe network AR implementation system comprising a mobile terminal and a central server. The mobile terminal is equipped with a camera, attitude sensor, RTK positioning module, motion tracking module, ultrasonic detection module, damage classification module, data shredding module, data storage module, displacement control module, and wireless communication module. Through the cooperation of the mobile terminal and the central server, the actual situation of the urban underground pipe network is displayed on the screen in AR mode. This facilitates the scheduling of manual inspections or drone checks, improves the efficiency of manpower and material resource allocation, avoids situations where workers are unable to access pipe locations, and allows for the rapid acquisition of accurate pipe network information. This reduces the difficulties in planning, construction, and maintenance of the pipe network, and minimizes the occurrence of pipe breaks during construction.

The invention comprises a machine learning-based optical system and methods for performing motion capture. The system comprises an optical sensor setup that provides raw, unstructured landmark inputs and relies on a neural network, trained for balanced regression, to denoise, label and complete them, estimating a richer set of refined landmark positions. The system and methods automatically calibrates the captured subject, and automatically refines the captured motions, improving the naturalism, smoothness and correcting capturing artifacts. The system and methods benefit from a balanced regression training scheme to improve said neural network's performance on long-tailed motion datasets.

The present invention provides a motion tracking device and a radiation irradiation system that can suppress changes in dose distribution and decreases in irradiation efficiency due to latency. [Solution] A motion tracking device that determines the position of the tracked object 55 and generates a signal to permit radiation irradiation to the target 50 when it is determined that the tracked object 55 is inside the gate range, wherein the gate range is different at the time when the tracked object 55 enters the gate range from outside to inside and at the time when it exits the gate range from inside to outside.

The application belongs to the field of motion tracking, and discloses a full-cycle motion tracking method and system based on multi-modal data mining. The application obtains multi-modal health data of a user in a preset evaluation period, constructs a health evaluation index matrix to calculate a dynamic weight and a health comprehensive index, can unify and fuse motion data, physiological morphology data and subjective feedback data, and overcomes the defects of single evaluation dimension and one-sided results of the prior art. The application calculates a motion energy value based on a motion segment, an intensity coefficient, an effective motion duration and a health change gain, can establish a correlation between motion input and health improvement results, and improves the accuracy of incentive feedback. The application maps the motion energy value to virtual pet growth resources, drives experience accumulation, grade promotion, appearance unlocking and action slot expansion, and can enhance the sustainability of the incentive mechanism.

A dynamic tracking system (1) comprises a contour detection unit (12), a video display unit (24), and a contour adjustment unit (25). The contour detection unit (12) detects a contour of an organism in frame images constituting a video, and performs a process for setting a plurality of contour points aligned along the contour for each frame image. The video display unit (24) displays, via a GUI (20), a video constituted by the frame images by overlaying the plurality of set contour points. The contour adjustment unit (25) is capable of adjusting the positions of the plurality of contour points in the displayed video via the GUI (20).

System and methods are provided for body motion tracking. The system includes one or more ultrasound systems configured to be worn by a subject and to acquire ultrasound data during motion of a first location on the subject. The system also includes one or more inertia measurement unit (IMU) systems configured to be worn on a second location on the subject and to measure inertia data associated with motion of the second location and a control system configured to integrate the ultrasound data and the inertia data to generate position data, the position data characterizing a motion of one of the first or second location on the subject.

System and methods are provided for body motion tracking. The system includes one or more ultrasound systems configured to be worn by a subject and to acquire ultrasound data during motion of a first location on the subject. The system also includes one or more inertia measurement unit (IMU) systems configured to be worn on a second location on the subject and to measure inertia data associated with motion of the second location and a control system configured to integrate the ultrasound data and the inertia data to generate position data, the position data characterizing a motion of one of the first or second location on the subject.

A method and a system for acquiring and reconstructing a medical image of a subject supported by a movable couch are provided, as well as an imaging arrangement, and a computer program for carrying out the method. The method for acquiring a medical image of a subject comprises steps of receiving medical image data of the subject, and receiving a sequence of camera images of the subject. The camera images are acquired using one or more optical cameras mounted onto the medical imaging device. The camera images are synchronized with the medical image data. The method also comprises extracting a couch motion from the camera images, which comprises detecting displacement and / or deformation of the couch, and transforming the detected displacement and / or deformation to form the couch motion. The method further comprises performing motion compensated medical image reconstruction of the medical image data using the couch motion.

Examples described herein relate to computer vision-assisted analysis of motion of a person. An optical device of a motion tracking system captures a calibration image of the person. The calibration image is processed to determine at least two calibration length values based on distances between anatomical landmarks associated with at least one body member. The optical device captures an exercising image of the person while the person performs a predetermined exercise. The exercising image is processed to determine at least two target length values based on distances between the anatomical landmarks associated with the at least one body member. A depth-related parameter associated with a target body member of the person is determined based on the calibration length values and the target length values. The depth-related parameter is used in the motion tracking system to track motion of the person with respect to the predetermined exercise.