4 results about "Visual capture" patented technology

The application provides a humanoid robot facial expression mapping and calibration method, the facial expression mapping method constructs a self-supervised discrete expression data set, trains a multilayer perceptron model based on the data set, realizes preliminary mapping from expression parameters to rudder control signals, extracts expression parameters in a real person expression data set, generates robot rudder control signals through the model, constructs a self-supervised time sequence expression data set based on a redirection method, trains a long short-term memory network model, and realizes time sequence mapping of continuous expressions. The facial expression calibration method uses a visual capture device to obtain robot facial expression parameters in real time, gradually optimizes the rudder control signal, and makes the expression parameter response approach the target value. Through data-driven modeling and visual feedback optimization, the application realizes high-fidelity mapping from semantic expression parameters to multi-rudder collaborative control and systematic calibration, effectively improving the naturalness, accuracy and long-term stability of the robot facial expression.

This invention relates to a system and method for constructing a multimodal human behavior perception dataset based on CSI (Computer-Sensitive Interface). The system includes a wireless sensing subsystem for acquiring first CSI data packets of the human body, a visual capture subsystem for acquiring first RGB video, first depth video, second RGB video, and second depth video, a Linux-based central control unit, and a multimodal post-processing unit for cleaning and enhancing 3D skeletal joint data, denoising and extracting features from CSI data, and generating hierarchical natural language text descriptions. This invention constructs a large-scale, multidimensional, high-fidelity human behavior perception dataset acquisition system by deeply integrating high-frequency, fine-grained wireless signals with visual and semantic ground truth, ensuring the logical coupling of high-dimensional CSI signals and visual data.

The application discloses a kind of intelligent pet washing machine based on multi-modal perception, to solve the problem of missing and false alarm in washing and protecting.The machine includes cleaning cabin main body, multi-dimensional perception modal construction unit, edge computing control architecture and hierarchical safety response execution mechanism.Through visual capture expression posture, combined with acoustic sensing based on voiceprint analysis, multi-modal fusion decision is realized using dynamic weight distribution mechanism.When the evaluation score is over standard, trigger the physical escape program composed of torsion spring, electromagnetic release lock and hydraulic damper to open the cabin door in seconds.The application solves the problem of sensor failure in complex environment, and significantly improves the safety guarantee and recognition robustness of pet washing and protection through software warning and mechanical closed loop.

The application discloses a kind of cerebral apoplexy rehabilitation training action standard degree real-time monitoring device, the device is by integrating inertial measurement, surface myoelectricity and visual capture module, the multimodal data of patient movement is synchronously collected, and by the real-time fusion analysis of deep learning model in edge computing unit, dynamic compare for preset standard action template, to accurately quantify joint range of motion, motion trajectory, muscle activation timing and posture stability Key indicators, such as, and provide immediate error correction guidance and compliance score through audiovisual feedback module;The application realizes high-precision monitoring of rehabilitation action full-dimension and objectification by the real-time closed loop constructed, effectively solves the problem that traditional method relies on subjective experience and feedback delay, greatly improves the standardization level of rehabilitation training and neural remodeling efficiency, provides intelligent technical support for clinical and home rehabilitation.