445 results about "Motion detection" patented technology

A multimodal intelligent agent system for dynamic environmental monitoring and user-centered support, consisting of: a multimodal sensor module configured to continuously acquire environmental and behavioral data from multiple input modalities, including at least one visual sensor, at least one acoustic sensor, at least one environmental conditions sensor, and at least one proximity or motion detection sensor, each generating modality-specific data streams representing visual images, audio waveforms, physical environmental parameters, and motion signatures within a monitored environment; a data preprocessing and fusion subsystem that is operationally coupled with the multimodal sensor module and configured to normalize, temporally align, and transform the modality-specific data streams into high-dimensional feature embeddings using a variety of encoders, wherein the visual encoder uses convolutional or vision transformer architectures, the audio encoder uses a spectral-temporal feature extractor, and the sensor encoder transforms raw analog data into context vectors suitable for multimodal alignment; a multimodal processing unit consisting of a transformer-based large language model (LLM) trained on paired multimodal datasets and configured to perform semantic fusion, context abstraction, and inference across the aforementioned aligned multimodal feature embeddings to generate a contextual understanding of environmental and behavioral states; an adaptive agent controller coupled to the multimodal inference processing unit and configured to instantiate, manage, and terminate a variety of task-specific intelligent agents, each agent being a software unit configured to perform a specialized function selected from meeting summarization, behavioral analysis, misplaced object detection, or environmental anomaly identification, with the agents dynamically interacting with the inference engine to retrieve contextually relevant multimodal embeddings for task execution; a personalization and adaptive learning subsystem consisting of a user preference database and a neural memory structure configured to update and refine model parameters based on user-specific interaction history, thereby enabling personalized output generation, prioritization of recommendations, and long-term behavioral adaptation; and An output generation interface is operationally connected to the adaptive agent controller and configured to produce multimodal output in textual, visual, and auditory form. The interface is capable of displaying human-readable summaries, notifications, and visual reconstructions of identified entities or environmental states.

The invention relates to an agricultural robot, and discloses an animal husbandry pushing robot autonomous navigation method based on a laser radar, which comprises a microsecond-level multi-sensor time synchronization architecture based on an FPGA (Field Programmable Gate Array); in a navigation layer, seamless switching between the GNSS and the laser SLAM is realized by constructing a virtual fusion observation value by utilizing extended Kalman filtering and a self-adaptive dynamic weight algorithm; in the sensing layer, an RGB-I multi-mode model fused with laser reflectivity and a biological micro-motion detection technology are adopted, and feed and biological obstacles are accurately distinguished; and in the execution layer, flexible self-adaptive material pushing is achieved in combination with material groove edge fitting and force-position hybrid control, and the navigation precision, the operation quality and the safety of the material pushing robot in the all-weather and unstructured pasture environment are effectively improved.

The invention discloses a screen structure, an intelligent ground screen, a monitoring method, a medium and a computer product. The stress layer is suitable for being in contact with a target object, the circuit board layer is arranged below the stress layer, the force conducting layer is arranged below the circuit board layer, the force sensing layer is arranged below the force conducting layer, the force sensing layer comprises a pressure sensor, the force sensing layer abuts against the force conducting layer so as to be suitable for monitoring pressure from the force conducting layer, and the force sensing layer is connected with the base. Wherein the stress layer comprises a mask structure and a force conduction structure, the force conduction structure is provided with two opposite ends in the direction from the base to the stress layer, the first end is connected with the mask structure, the second end is connected with the force conduction layer so that the pressure of the mask structure can be conducted to the force conduction layer, the circuit board layer is provided with a through hole, and the force conduction structure penetrates through the through hole. According to the invention, the motion state of the target object can be accurately monitored in real time, and a high-sensitivity and high-precision circuit system can be protected from being damaged in frequent high-load motion detection.

The invention discloses an epilepsy signal identification method and system based on multi-modal information of wearable equipment. The method comprises the following steps: firstly, preprocessing acquired multi-modal physiological signal data; calculating a time-frequency feature through a sub-band analysis coefficient, extracting a time domain feature, a frequency domain feature and a nonlinear feature after reconstruction, and constructing a multi-modal feature matrix; obtaining an action feature matrix through a time-frequency feature threshold classifier; performing T test, correlation analysis and recursive feature elimination, and screening to obtain a final training set and an optimal feature list; respectively training an LSTM attack detection model and a random forest motion detection model, and constructing a serial ensemble learning framework; and finally, outputting a risk value based on a sliding window, triggering an alarm when the risk value continuously exceeds a threshold value, and starting a misinformation suppression mechanism in a non-response period. According to the method, non-attack motion interference is filtered through a designed serial integrated learning framework, the false alarm rate of the system is remarkably reduced, meanwhile, high detection sensitivity and accuracy are kept, and the real-time processing efficiency and practicability of the system are improved.

The invention relates to a pressing plate operation behavior analysis and error prevention method and system based on image recognition and machine learning. The method comprises the following steps: acquiring a pressing plate operation area video stream through image acquisition equipment, and segmenting a video into independent operation event segments based on motion detection and trajectory analysis; extracting key point time sequence data of hands of an operator by using a human body posture estimation model, and constructing a dynamic feature sequence fusing a spatial relationship, kinematics and posture semantics; performing multi-level similarity comparison on the dynamic feature sequence and a standard operation template, and judging operation compliance by a machine learning model in combination with a dynamic threshold value; triggering graded early warning and intervention according to a judgment result; and an incremental learning mechanism is adopted, and the template and the threshold value are adaptively optimized based on historical data. According to the invention, accurate and intelligent analysis and active error prevention of the whole operation process of the pressing plate are realized, and the safety level of electric power operation is effectively improved.

The invention relates to the technical field of motion detection alarm, in particular to a multi-agent fusion perception area intrusion abnormity alarm method and system, and the method comprises the following steps: collecting a target coordinate and a timestamp, integrating and sorting tracks, analyzing the direction and time change, judging the stability, recognizing an induction behavior, and screening and verifying the abnormity. According to the method, through integration of the spatial position and time information of the multi-source sensing intelligent agent, the continuous track of the target is reconstructed, the integrity identification of the motion behavior is enhanced, and the track direction change and time interval linkage analysis is carried out, so that the sensing depth of the behavior trend is improved; multi-dimensional recognition of abnormal behaviors is achieved through track stability and regional stay state linkage judgment, continuous conditions are introduced into abnormal verification to filter accidental interference, alarm output is matched with a regional strategy based on a verification result, the accuracy and robustness of intrusion detection are effectively improved, and the practical requirement in a high-dynamic scene is met.

Systems and techniques are described for image signal processor motion detection. In various examples, first image data including pixel values may be generated, where each pixel value is associated with a respective color tag of a color filter array. A first set of the pixel values corresponding to a first block may be determined. A second set of pixel values may be determined based on a respective pixel value of the first set and the respective color tag associated with that respective pixel value. A first intensity value associated with the first block may be determined based on the second set of pixel values. A second intensity value associated with a reference block may be determined. A comparison value representing a difference between the first intensity value and the second intensity value may be determined. A signal indicating detected motion may be sent based on the comparison value.

The invention discloses a massage quantization glove based on multi-signal fusion and a real-time feedback control system thereof. The massage quantization glove comprises a glove body, a double-layer differential sensing unit, a perturbation excitation unit, a motion detection unit, a signal processing and fusion unit and a feedback interaction unit. The double-layer differential sensing unit is composed of an outer-layer pressure sensing film, an isolation elastic layer and an inner-layer pressure sensing film and is used for collecting overall contact force and differential response signals. The perturbation excitation unit applies low-amplitude disturbance in the massage process, so that soft tissue viscoelasticity characteristics are extracted; the motion detection unit collects hand motion information and performs inertia compensation; the signal processing and fusion unit is used for denoising and analyzing the multi-source signal to generate a dose index and a hardness grade; and the feedback interaction unit prompts an operator through visual sense, auditory sense or tactile sense. Real-time quantification and feedback of massage dosage are realized, tissue hardness change can be reflected, excessive massage is avoided, curative effect consistency is improved, and massage operation standardization is promoted.

The invention discloses an electric power overhaul video action detection method based on a multi-scale state space, and the method comprises the steps: firstly collecting long video data in an electric power overhaul process, segmenting the long video data into a plurality of time sequence segments, and carrying out the spatial feature coding and high-dimensional mapping of the plurality of time sequence segments, and obtaining a time sequence token sequence; then, an electric power overhaul video action detection network is constructed and trained, and the electric power overhaul video action detection network comprises a time sequence multi-scale coding module, a scale perception state fusion device and a multi-label prediction layer; and finally, performing action detection on a time sequence token sequence corresponding to the electric power overhaul long video data to be detected by adopting the trained electric power overhaul video action detection network to obtain an action category detection result. According to the method, timing sequence multi-scale coding, state space modeling and a scale perception feature fusion mechanism are fused, the short-time sudden action and the long-range dependency relationship can be captured at the same time, and the recognition capability and the positioning precision of the complex concurrent action in the electric power overhaul video are remarkably improved.

The invention relates to the field of image data processing, and provides a steam boiler gas leakage detection method based on image processing, which comprises the following steps: setting an image acquisition unit, covering a predetermined leakage risk area together, acquiring corresponding reference images under different production working conditions, and establishing an image reference library covering a target area; the method comprises the following steps: dividing a boiler operation time axis into a plurality of production states, calling corresponding reference images according to different states, and carrying out difference, partition comparison and motion detection on the real-time acquired images to obtain suspected leakage cloud cluster areas in the corresponding states; arranging a condensate water indication patch, collecting a patch image, extracting through color, brightness and texture features to form a patch humidity change curve, carrying out multi-source information fusion on the patch humidity change curve, time sequence features and production time states, and outputting a corresponding steam leakage risk level; and generating alarm information according to the steam leakage risk level, and recording and archiving the alarm information in a monitoring and management system for energy consumption analysis and risk tracing.

The invention belongs to the field of dangerous rock monitoring, and provides a dangerous rock monitoring method, device, equipment and medium based on wide-area electric shock amplitude frequency, and the method comprises the following steps: carrying out high-frequency wide-area electromagnetic method detection, electromagnetic radiation monitoring, micro-motion detection and vibration signal monitoring on a dangerous rock monitoring area; based on the high-frequency wide-area electromagnetic data at different time points, whether resistivity difference abnormity exists or not and whether an electromagnetic radiation abnormal event occurs or not are determined; based on the micro-motion data at different time points, whether speed structure difference abnormity exists or not and whether a vibration abnormal event occurs or not are determined; and when the electromagnetic radiation abnormal event and the vibration abnormal event are synchronous in occurrence time and consistent in spatial positioning, determining that the event is a rock crushing event. Through multiple detection means, broadband range real-time monitoring of electromagnetic signals and vibration signals is realized, abnormal signals generated by internal changes of rocks can be detected and identified to the maximum extent, the dangerous rock disaster-pregnancy process is effectively monitored, ground disaster missing report is reduced, and the early warning success rate is improved.

The invention discloses a thermal infrared imager intelligent temperature measurement platform management method and system. The method comprises the following steps: S1, information acquisition and multi-modal data binding; s2, encoding and encrypting data; s3, wireless transmission and decryption are carried out; s4, the server side performs intelligent processing; s5, result distribution and storage; according to the invention, through deep fusion of multi-modal data binding and environment interference parameters, the motion detection and temperature pre-judgment process can dynamically adapt to interference changes in a complex scene; a multi-modal fusion dynamic threshold algorithm, a space-time attention enhancement model and a layered time sequence temperature prediction model are integrated, the full-dimension requirement from real-time monitoring to long-term trend analysis is covered, and the intelligent level and scene adaptability of the system are remarkably improved; and a whole-process system architecture of sensing, transmission, processing, storage and display is constructed, so that the platform has high efficiency of data processing and convenience in use.

Implementations described herein relate to a method, system, and computer-readable medium for generating animation for a 3D avatar from input video and audio captured on a client device. A camera may capture facial video, and a trained face detection model and a trained regression model output a set of video FACS weights, head pose, and facial landmarks that will be converted into animation for the 3D avatar. In addition, a microphone may capture audio emitted by a user, and a trained face motion detection model and a trained regression model output a set of audio FACS weights. In addition, a blending term is provided for identifying time progression in the audio. A modular blending component blends the video FACS weights and audio FACS weights based on the blending term to create final FACS weights for animating the user's avatar, a character's clothing, or another animation-enabled construct.

The invention discloses a brain-computer interface manipulator motion detection system for disturbance of consciousness assessment, which belongs to the technical field of disturbance of consciousness assessment and specifically comprises an electroencephalogram acquisition device for acquiring original electroencephalogram signals when a patient executes motor imagery tasks containing different hand action instructions; the dynamic feature extraction module generates a motor imagery activation map by calculating the energy distribution change of a preset frequency band; the driving instruction generation module calculates the space-time matching degree of the map and a preset action instruction and generates a manipulator driving instruction; the manipulator control module is used for controlling and executing a composite action positively correlated with the instruction strength, and the action is formed by combining basic grasping and multi-joint coordination actions in proportion; the motion capture device records track changes, and the ratio of the number of the joints exceeding the threshold value to the motion duration serves as a consciousness activity index; the disturbance of consciousness grading module determines a grading result according to the fluctuation range of the index in the continuous period; the method provides an objective and accurate quantification means for disturbance of consciousness assessment.

The invention discloses an edge computing-oriented ultra-high-definition video dynamic concentration and lightweight transmission system, and provides a lightweight transmission mechanism based on content awareness and closed-loop feedback. The system performs frame-level motion detection and semantic analysis on a video stream at an edge node, extracts motion intensity, object density and key event characteristics, dynamically calculates a concentration factor in combination with task priority, realizes intelligent retention of key frames and cutting of redundant frames, and generates a concentrated video stream; meanwhile, the coding rate is adaptively adjusted according to the real-time uplink bandwidth, and transmission parameters are optimized through a bandwidth-quality tradeoff function; a receiving end evaluates the actual quality and feeds back the actual quality to an edge node, and dynamically adjusts a concentration and coding strategy to form closed-loop control of sensing-concentration-transmission-feedback; the system is suitable for a large-scale intelligent video analysis scene, the bandwidth occupation and the storage overhead are remarkably reduced, and the system response efficiency and the key information retention rate are improved.

A data processing device for motion-dependent image processing in a medical observation device is configured to retrieve an input set of input images from a same time sequence, determine a stationary input image segment representing stationary image content in the input images of the input set by applying a motion detection scheme to the input set, determine a stationary output image segment in an output image having a same location in the output image as the stationary input image segment has in one of the input images of the input set, and determine an intensity value of an output pixel of the output image in the stationary output image segment from a combination of intensity values combining corresponding input pixels from different input images of a subset of the input set with each other. The corresponding input pixels lie within the stationary input image segment.

To provide a portable electronic device and operating method that are easy to use. [Solution] This printing system comprises a printer and a terminal capable of wireless communication with each other, and transmits data wirelessly from the terminal to the printer for printing. The printer comprises a portable printer body, a motion detection unit that detects the movement of the printer body, and a control signal transmission unit that transmits a first control signal to the terminal when a first movement is detected by the motion detection unit, and transmits a second control signal to the terminal when a second movement is detected by the motion detection unit. The terminal comprises a display unit, a display control unit that controls the display of the display unit, and a control signal receiving unit that receives control signals from the printer. When the control signal receiving unit receives a first control signal, the display control unit of the terminal causes a first operation screen to be displayed on the display unit. When the control signal receiving unit receives a second control signal, the display control unit causes a second operation screen to be displayed on the display unit.

A solid-state lighting fixture assembly having a lighting fixture with a socket configured to receive a plug associated with one or more accessories to allow for easy in-field mounting of accessories, e.g., controls, onto installed lighting fixtures. The socket may be internally electrically connected to an auxiliary power output of a driver and / or to a battery power pack within the lighting fixture assembly, thereby providing direct-current voltage power for the accessory and, also, allowing for signal transmission to and from the accessory. Each accessory includes one or more sensors and communication components to provide the connected lighting fixture assembly with specific capabilities including, but not limited to, motion detection, ambient light level detection, ambient temperature measurement and wireless communications. The wireless communication can also be used to control one or a group of lighting fixtures and transmit sensor data associated with, for example, monitoring space utilization and asset tracking.

In various examples, systems and methods are disclosed that perform motion detection across image frames, such as optical flow determination, to synchronize an asynchronous frame with respect to a target time for the asynchronous frame. For example, image frames from a sensor can be processed by an optical flow accelerator to detect displacement across the image frames, and the displacement can be used to interpolate a modified frame at the target time. This can be used to perform data collection and combining operations such as stitching and / or reconstruction. The synchronization can be performed from sensor data from sensors such as cameras, LIDAR sensors, and / or RADAR sensors.

This invention discloses a ship motion detection system, including a ship motion angular displacement detection system comprising a lateral tilt sensor, a longitudinal tilt sensor, and a heading sensor installed on the ship; a target tracking and observation system comprising a target tracking servo gimbal and a target observer installed on the ship; and a data acquisition, calculation, and storage system for acquiring and storing the ship's roll, pitch, and bow signal data measured by the ship motion angular displacement detection system, and for calculating and storing the ship's sway, pitch, and heave motion data. This invention also discloses a ship motion detection method based on the above system. This invention enables highly reliable and accurate measurement of ship motion data in waves, further improving the compensation accuracy of wave compensation boarding bridges on wind power maintenance vessels.

The invention relates to a cambered surface detection platform which comprises a rack, a conveying assembly, a position adjusting assembly, a position detection assembly, a first cambered surface detection assembly, a second cambered surface detection assembly and a control assembly. The conveying assembly is installed on the rack and arranged in the X-axis direction of the rack in a sliding mode. The position detection assembly, the first cambered surface detection assembly and the second cambered surface detection assembly are sequentially installed on the rack along the advancing route of the conveying assembly. The position adjusting assembly is installed on the conveying assembly. The conveying assembly, the position adjusting assembly, the position detecting assembly, the first cambered surface detecting assembly and the second cambered surface detecting assembly are electrically connected with the control assembly. According to the cambered surface detection platform, each to-be-detected special-shaped component with the complex curvature can be accurately positioned, fitting motion detection and defect detection of the special-shaped component with the complex curvature are achieved, the detection time is shortened, and the detection efficiency is improved.

The invention relates to the technical field of artificial intelligence, in particular to an action detection method and equipment based on a multi-modal large model. Acquiring an inspection video recording the inspection process of the on-duty personnel, pre-inspecting the inspection video based on a time sequence action detection model, determining a first probability value of a target action existing in a video segment corresponding to each prediction time range, and determining a second probability value of the target action existing in a video segment corresponding to each prediction time range for each prediction time range; and if the first probability value corresponding to the prediction time range does not meet the preset threshold requirement, detecting a video segment corresponding to the prediction time range based on a multi-modal large model to obtain a detection result used for describing a target action existing in the corresponding video segment, the problems of low accuracy and low efficiency of traditional manual quality inspection are effectively solved, and the accuracy of action detection is improved by utilizing a multi-modal large model secondary judgment mode.

The motion detection device (5) includes a first support (51), a second support (52) that moves relative to the first support, a power generation sensor (100) disposed on the first support, and a magnetic field generating source (400) supported on the second support. The power generation sensor includes a magnetic wire (110), a coil (120), and a magnetic flux conducting plate (130, 131). The magnetic flux conducting plate includes an axially orthogonal portion and an axially parallel portion, and has a wire arrangement portion that fixes the axially orthogonal portion and both ends of the magnetic wire. The power generation sensor is configured such that the side opposite to the magnetic wire is set as the detection area (140) relative to the axially parallel portion. The magnetic field generating source has multiple magnetic poles. Magnetic poles of different polarities enter the detection area sequentially along a track (30) parallel to the axis of the magnetic wire and are opposite to the power generation sensor. The magnetic flux direction of each magnetic pole is perpendicular to its direction of movement and is the direction that intersects with the magnetic wire.

Systems, methods, and software to process tiered motion detection for video surveillance are provided herein. In one implementation, a video processing computing system is configured to identify a request for an object to enter a physical area and select a portion of the physical area available to the object based on the request. The video processing computing system is further configured to monitor movement of the object in the physical area using one or more video streams from one or more cameras and determine that the object moved outside the portion of the physical area available to the object based on the monitored movement. The computing system also generates an alert in response to the determination that the object moved outside the portion of the physical area available to the object.

To provide a moving body detection device or the like capable of detecting a moving body by easily setting a detection area for detecting the moving body.SOLUTION: The moving object detection device 10 includes a specifying unit 11 that acquires an image captured by the camera 1 and specifies a predetermined region satisfying a predetermined condition in the image, a setting unit 12 that sets the predetermined region specified by the specifying unit 11 or a region other than the predetermined region specified by the specifying unit 11 in the image as a detection region in which a moving object is detected, and a detection unit 13 that detects a moving object in the detection region.SELECTED DRAWING: Figure 2

The application discloses a kind of single-photon TOF image sensors for laser radar, including reconfigurable pixel array, dynamic reconfigurable circuit, real-time feedback control system;Reconfigurable pixel array is constructed based on field programmable array FPGA technology, each pixel unit is integrated with configurable single-photon avalanche diode SPAD, amplifier, integrator and control logic circuit, by programming to the internal logic of FPGA, change pixel operating mode and parameter, and pixel unit can be configured as unit with specific function, pixel for edge detection and motion detection, in the application, flexible reconfigurable pixel configuration: with field programmable array FPGA technology, the photosensitive area of pixel unit, integration time and gain and other key parameters can be flexibly adjusted according to actual demand, pixel unit can also be configured as unit with specific function such as edge detection, motion detection.

The application relates to the medical imaging technical field and discloses a motion detection method and device for a perfusion scanning process and a CT scanning device, wherein the motion detection method comprises the following steps: acquiring an image of a current scanning circle; performing skull region segmentation on the image of the current scanning circle to obtain a skull mask image of the current scanning circle; comparing the skull mask image of the current scanning circle with a target skull mask image to determine an overlapping degree index; and determining the motion condition of the patient's head according to the overlapping degree index. The image reconstructed by the current scanning circle is acquired in real time during the scanning process, the image of the current scanning circle is subjected to skull region segmentation to obtain a skull mask image, and the overlapping degree index of the skull mask image of the current scanning circle and the target skull mask image is determined, so that the motion condition of the patient's head can be quantitatively evaluated, and the motion detection accuracy is improved.

The invention comprises a device and a method for detecting and evaluating the movements of a person over time and for generating feedback to the person, comprising detecting the person by means of a motion detection sensor, generating an observation point model of observation points for the detected person, evaluating the detected movements with regard to defined movement deviations in a first time interval, and outputting feedback to the person by means of an output unit in a second time interval following the first time interval regarding the determined movement deviation.