263 results about "Single frame" patented technology

The invention discloses a single-frame infrared thermal imaging building outer wall hollowing detection method and system based on heat flow evaluation. The method comprises the following steps: acquiring a single-frame infrared thermal image and a visible light image which are synchronously acquired; generating an infrared thermal imaging sequence based on the single-frame infrared thermal image and the Green function of the heat conduction control equation; performing time-space frequency domain transformation and column harmonic function inversion on the infrared thermal imaging sequence, and inversely transforming back to a time-space domain to generate a virtual heat flow image sequence; sequentially carrying out binarization processing and discrimination function enhancement processing on the single-frame virtual heat flow image to obtain an outer wall enhanced binarization image; identifying an interferent from the visible light image by adopting a target detection network; and carrying out registration and mapping on an identification result in the visible light image and the infrared thermal image, and removing interferents in the outer wall enhanced binarization image to obtain a pure outer wall binarization image. The method has the advantages of high environmental adaptability, high recognition precision and the like, and is suitable for safety detection and maintenance of building exterior walls.

The invention discloses a WebGL-based mass data particle system rendering method and device, and belongs to the technical field of computer graphic processing. The method comprises the following steps: firstly, selecting the type of a particle emitter according to scene requirements, then constructing a primitive object based on points or quadrangles, and configuring three-dimensional coordinates and texture parameters; aggregation rendering is carried out on a single-frame primitive array through a WebGL vertex shader and a fragment shader, and the drawing calling frequency is reduced; the method comprises the steps of dynamically adjusting particle attributes, including position compensation, color gradient and explicit-implicit control, determining a rendering form and playing time of an animation according to requirements of an actual application scene, and supporting fine configuration of a single particle, including texture animation, dynamic scaling and rotation parameters. When a large amount of data is processed, on the premise of ensuring the rendering quality, the rendering efficiency can be remarkably improved, the consumption of a memory and GPU resources can be reduced, the response time of the system can be optimized, and meanwhile, the interaction experience of a user can be improved.

The invention discloses a space-time speckle projection three-dimensional imaging method based on multi-frame optical flow alignment. Firstly, a projector based on DLP is used for projecting a space-time speckle pattern to a measured scene, and a binocular camera synchronously collects a three-dimensional space-time speckle image. The calibration parameters of the binocular camera are used to carry out stereo correction on an acquired original speckle image, and a parallax image is generated frame by frame in combination with a coarse-to-fine single-frame speckle matching strategy. And estimating a two-dimensional inter-frame displacement field between continuous disparity maps by using an optical flow method by taking an intermediate frame disparity map as a reference, compensating motion artifacts in a space-time speckle image, and ensuring strict space-time registration of a dynamic target. And based on the speckle image after motion correction, a speckle matching strategy is expanded to a time-space domain, and high-precision multi-frame three-dimensional measurement of a complex dynamic scene is realized. The method is suitable for performing rapid and high-precision three-dimensional modeling on a moving target in an unstructured environment, and can perform accurate three-dimensional measurement on a high-speed dynamic target undergoing any translation or rotation motion.

The invention discloses a video stream defogging method and system for 5G remote control, and relates to the technical field of image enhancement. The method comprises the following steps: acquiring a foggy video in real time; inputting the single-frame foggy video into a pre-trained monocular depth estimation neural network, and reasoning to obtain a depth map with the same size as the input single-frame foggy video; performing close-shot and long-shot region division on the scene of the current foggy video frame according to the depth map to obtain a region mask with the same size as the depth map; based on the region mask and the foggy video, calculating to obtain an atmospheric light parameter; calculating the transmissivity of each pixel according to the distance estimation result of each pixel in the depth map, and obtaining a transmissivity map with the same size as the depth map; based on the depth map, the atmospheric light parameters and the transmissivity map, adaptive calculation is performed on the foggy video to realize defogging, and a defogged clear video frame is obtained; the method can adapt to different depth-of-field fog effects, realizes different depth-of-field defogging, and outputs clear video frames.

The invention provides a cross-platform video decoding method and device, computing equipment and a computer readable storage medium, and the method is combined with a factory mode to completely package bottom layer differences of all platform types, and an application layer developer does not need to care about the bottom layer platform differences. The optimal implementation can be automatically selected on different engines and platforms through a uniform API (Application Program Interface); during rendering, a single-frame memory management strategy is used, and only one frame which is currently displayed is reserved in a memory; and in the aspect of performance, the advantages of a multi-thread platform and the parallel computing characteristics of the GPU are fully utilized. According to the embodiment of the invention, through deep fusion of a cross-platform soft decoding architecture, single-frame memory optimization, multi-thread parallel, GPU acceleration and other technologies, perfect balance of cross-platform, high performance and low memory is realized, and the development efficiency of the whole project is improved.

A method for training a model for generating a representation of long-term motion from a text input comprises: training a motion encoder of an autoencoder to compress and map an input motion into a latent representation comprising a sequence of latent vectors in a discrete latent space, each latent vector representing a fixed length of motion; training a quantization module to quantize the latent vectors to a sequence of quantized latent vectors in quantized latent space; and training a motion decoder to reconstruct the quantized sequence as a sequence of single-frame pose representations. A text encoder is trained to predict a latent sequence conditioned on a text input and a duration using the mapped latent representation as a target.

The invention discloses a single-frame three-dimensional imaging method based on multi-frequency RGB (red, green and blue) stripe compression. According to the method, three groups of structured light stripe patterns with relatively prime frequencies and different directions are respectively embedded into RGB channels by utilizing channel characteristics of a color camera, the patterns are switched at a high speed by a projector, dynamic superposition is completed within single-frame exposure time of the camera, space compression acquisition of time domain information is realized, and a color superposition image fused with multiple pieces of time slice information is obtained. According to the invention, a multi-stage deep neural network architecture is designed to realize separation of fringe images of a color superposition image at different moments, phase information is accurately extracted from the decomposed fringe images, and finally unambiguous high-speed three-dimensional imaging in dynamic scenes at different moments is realized. According to the method, the time resolution of three-dimensional imaging can be remarkably improved without improving the frame rate of the camera, meanwhile, the space precision and the system stability are considered, and good universality and expandability are achieved.

The invention discloses a dam infrared thermal imaging leakage intelligent identification method fused with dynamic frame difference, and the method comprises the steps: building a frame difference graph based on an improved OTSU algorithm through a thermal infrared image sequence, so as to enhance the temperature micro-change perception capability, and achieving the high-precision identification of a leakage abnormal region through combining with a YOLOv8 model; meanwhile, the area of an abnormal region in a frame difference image sequence is extracted, the leakage evolution process is dynamically described, and a quantitative judgment mechanism is constructed in combination with fitting of an area change trend and t test, so that the accuracy and robustness of leakage outlet recognition are improved. Compared with a traditional visible light detection means, the method has earlier response capacity under various complex working conditions, the misjudgment rate and the missed judgment rate in single-frame recognition are remarkably reduced, and powerful technical support and engineering reference are provided for intelligent recognition and safety management of earth and rockfill dam leakage.

A system and method of encoding at least a plurality of tensors forming a hierarchical representation for a single frame into a bitstream. The method comprises deriving a first unit of information from a plurality of tensors forming the hierarchical representation, the plurality of tensors including at least a first tensor and a second tensor, feature maps of the first tensor having a larger spatial resolution than feature maps of the second tensor and encoding, in a first mode, at least the first unit of information into the bitstream. In a second mode, the method also comprises deriving a second unit of information derived from the first tensor; and encoding, the second unit of information and the first unit of information into the bitstream.

The invention discloses a cutting machine tool wear detection method and system based on image recognition, and relates to the technical field of wear detection, and the method comprises the steps: collecting multiple tool nose images in a short time window through triggering signal control, obtaining the time sequence information of a tool state, and eliminating the interference through combining with an image preprocessing and time sequence alignment technology. A U-Net model is used for precisely segmenting a single-frame image to obtain a tool abnormal area, dynamic association among multiple frames of images is deeply excavated through connected component analysis and time sequence consistency verification, a real abrasion area is screened out from a multi-frame sequence, and finally a tool abrasion detection result is obtained. Therefore, non-wear interference can be effectively distinguished and eliminated, and the defects that a traditional method is insufficient in precision and prone to false detection and missing detection are overcome, so that the accuracy and robustness of a detection result are remarkably improved, false alarm and missing alarm are avoided, and the intelligent production requirement of the modern industry is met.

The invention discloses a video-based method for supervising behaviors of people in a bank, which comprises the following steps of: acquiring a video sequence by using a camera in the bank, performing single-frame segmentation on the video sequence to obtain a current frame image of the people in the bank, and performing attitude estimation on the people in the bank in the current frame image by using an attitude positioning model; wherein the attitude positioning model comprises a first attitude positioning module and a second attitude positioning module; the first posture positioning module is used for acquiring the spatial relationship of key points of people in the bank in the current frame image, and the second posture positioning module is used for acquiring the current frame human body posture of the people in the bank by using the spatial relationship of the key points of the people in the bank; and finally, the current frame of human body posture is used for supervising the abnormal behavior of the personnel in the bank at present, the spatial relationship in the image is effectively utilized, the accuracy of the result is improved, and in addition, the precision and efficiency of supervising the personnel in the bank are improved by improving the training strategy.

The invention belongs to the technical field of radar data processing, and relates to a ground target elimination method for two-dimensional phased array low-altitude detection, a medium and electronic equipment. The method comprises the following steps: transmitting a single-frame waveform composed of an airspace detection wave position and a ground sidelobe rejection wave position; selecting the detection point with the maximum power as an effective detection point of the airspace detection wave position, and judging the other detection points as ground side lobe detection points and removing the ground side lobe detection points; and rejecting effective detection points with ground sidelobe rejecting wave positions of which the power is higher than that of the effective detection points from the detection points of the airspace detection wave positions. According to the method, the unmanned aerial vehicle batch starting time is greatly shortened, and unmanned aerial vehicle track batch starting is realized; the contradiction between the detection power and the batch starting time is decoupled, and the ground side lobe target is eliminated; the beam resource utilization rate is improved, and the detection response speed of the radar system to the unmanned aerial vehicle target is improved.

The invention discloses a lightweight traffic sign recognition method fusing time sequence characteristics in a shielding scene, and relates to the field of computer vision and intelligent traffic, in particular to a traffic sign recognition technology. Respectively constructing a single-frame data set with slight occlusion and a time sequence data set with severe occlusion; for a street scene image containing a complex background, training a lightweight target detector YOLOv8-N based on an existing bounding box label in a data set; secondly, a depth separable convolution structure with MobileNetV2 as a trunk network is adopted, and a high-dimensional feature map is extracted from the candidate mark image; then, a space attention mechanism is introduced, weighted correction is carried out on input features, an unshielded region is strengthened, and a shielded and noise region is suppressed; and finally, extracting a feature sequence of a historical frame of a heavily shielded sample, and inputting the feature sequence into an extended long-short-term memory network xLSTM for time sequence fusion.

The invention discloses a single-frame unmanned aerial vehicle image pixel positioning method and system based on an elevation map, and relates to the technical field of unmanned aerial vehicle image processing and geographic positioning, and the method comprises the steps: obtaining a single-frame original image shot by an unmanned aerial vehicle, unmanned aerial vehicle attitude information during shooting, camera internal and external parameters, and a digital elevation map of a shooting region; according to the internal reference of the camera, converting the pixel coordinate of the target pixel in the original image into a normalized plane coordinate system of the camera, and carrying out coordinate distortion correction to obtain the back projection point coordinate of the target pixel; converting a camera-unmanned aerial vehicle body coordinate system and a body-geographic inertial reference coordinate system according to camera external parameters and unmanned aerial vehicle attitude information to obtain normalized ray direction vectors corresponding to target pixels; an earth surface height constraint is constructed based on a digital elevation map, and an intersection point of a ray and the ground is determined by performing iterative approximation on a space point along a ray direction. According to the invention, rapid and accurate conversion from the single-frame unmanned aerial vehicle image pixel to the geographic coordinate can be realized.

The invention provides a servo mechanism control system and method based on TSN network communication, and relates to the field of servo mechanism control. According to the system, a TSN network communication interface is adopted, and 1Gbps instruction receiving and sending can be achieved. Through optimization mechanisms such as time synchronization, flow scheduling and frame preemption, it is guaranteed that key data streams arrive at destinations within strictly specified time, delay and jitter are extremely low compared with RS422, only the us level exists, and state feedback of a servo mechanism is more real-time and accurate; in a communication period of 1ms, the maximum transmission of a single frame at a rate of 1Gbps can achieve 1500 bytes, and the capacity is greatly improved compared with that of RS422, so that a servo mechanism can return more state information; an optical cable is adopted as a communication medium, electromagnetic interference is avoided, and the real-time performance and stability of the communication process of the servo mechanism are guaranteed; and for a high-dynamic precise control scene, the communication period can be shortened to 500us, the state feedback of the servo mechanism is real-time, and further precise control is facilitated. The problems that a traditional servo mechanism is low in communication rate, limited in single-frame capacity, poor in anti-interference capacity and the like are solved.

Methods, systems, and apparatus, including medium-encoded computer program products, for computer aided design of physical structures include: rendering, to a display device of a first user, a first user's view into an extended reality environment, the first user's view being generated using a first pose being tracked for the first user; identifying that a first avatar associated with the first user has entered a shared perspective mode with a second avatar associated with a second user of the XR environment, wherein the shared perspective mode has a single frame of reference in the XR environment that is shared by the first user and the second user; and performing, while in the shared perspective mode, the rendering to the display device of the first user.

This disclosure provides a method and system for automotive diagnostic services based on a modular UDS protocol, relating to the field of automotive UDS development technology, including a host computer, PCAN, and an electronic control unit (ECU). The ECU includes a network layer and a session layer. The host computer sends diagnostic messages to the ECU via PCAN. After receiving the diagnostic message from the host computer, the ECU distinguishes the network protocol control information type of the diagnostic message, determines whether the current network state of the network layer allows receiving the diagnostic message frame, and determines whether the addressing mode, session mode, and security level are equal to the ECU's configuration information. If the network layer allows reception, the session layer determines whether the ECU supports the service. After the session layer confirms the response type to be sent, the network layer sends one or more frames according to the protocol type. This disclosure enables rapid iteration when adding or removing UDS services, reducing code modifications.

This utility model discloses a wall frame structure for preventing cracks and leakage, belonging to the technical field of wall frame technology. It includes a casting slab, a reinforcing plate, a positioning structure, a feeding structure, casting holes, transverse reinforcing bars, longitudinal reinforcing bars, a main forming plate, and a secondary forming plate. The reinforcing plate abuts against the casting slab. The casting hole is located on the casting slab. The positioning structure is set on the casting slab. The transverse reinforcing bars are placed within the casting slab through the casting hole. The longitudinal reinforcing bars are placed within the casting hole and abut against the transverse reinforcing bars. The feeding structure is located on the reinforcing plate and is used to feed material into the casting hole. The main forming plate abuts against the side of the casting slab away from the reinforcing plate, and the secondary forming plate abuts against the side of the reinforcing plate away from the casting slab. This utility model, by forming a single frame with the reinforcing plate and casting slab, ensures uniform internal stress during use, greatly enhancing the overall structural strength and effectively improving the wall's resistance to cracks and leakage.

The invention discloses a reflective column scene abnormal depth detection method based on multi-modal fusion, and belongs to the technical field of abnormal depth detection. The method comprises the following steps: firstly, aligning RGB and IR images with different sizes, extracting a ground area in the RGB image through a segmentation network, and mapping the ground area into a depth map to accurately identify the ground; for the problem that the ground near the reflective column is difficult to distinguish, more reliable ground identification is realized by introducing a segmentation network. Meanwhile, for other abnormal noise points in the depth map, a method for screening by using the standard deviation relative difference of the two-frame depth difference and the single-frame standard deviation is provided, so that the robustness of random noise is enhanced. According to the method, the defects of an existing multi-mode method in a high-reflection scene are overcome, and a new solution thought is provided for quality improvement of the ToF depth data in a complex environment.

The application discloses a kind of single frame unmanned plane image pixel positioning method and system based on elevation map, it is related to unmanned plane image processing and geographic positioning technical field, obtain the single frame original image of unmanned plane shooting and the digital elevation map of the shooting area when unmanned plane attitude information, camera internal and external parameters, shooting;According to camera internal parameter, the pixel coordinates of target pixel in original image are converted to camera normalization plane coordinate system, and target pixel back projection point coordinates are obtained after coordinate distortion correction;According to camera external parameter and unmanned plane attitude information, camera-unmanned plane body coordinate system, body-geographic inertial reference coordinate system conversion is carried out, and the normalized ray direction vector corresponding to target pixel is obtained;Based on digital elevation map, construct ground height constraint, by iterative approximation to space point along ray direction, determine the intersection of ray and ground.The application can realize the fast and accurate conversion of single frame unmanned plane image pixel to geographic coordinate.

The invention discloses a semantic map construction method based on a camera-laser radar, and belongs to the technical field of robot perception and autonomous navigation, and the method comprises the steps: carrying out the hardware configuration, so as to achieve the perception and time synchronization of the camera and the laser radar; performing sensor calibration on the camera and the laser radar; constructing a local overlapping frame point cloud according to the camera image and the laser radar point cloud; open set 2D semantic extraction of an open word list is realized under single frame and time sequence joint constraint; and carrying out 2D-3D assignment and cross-frame instance fusion to construct a semantic map. In order to solve the problems that in the prior art, geometric advantages of a laser radar are not fully utilized, open set targets of indoor intelligent scenes are difficult to adapt, and the like, the invention provides an overall scheme capable of realizing engineering landing. The method has the advantages that the open set semantic coverage capacity is high, 2D-3D assignment noise is low, cross-frame fusion is stable, semantic retrieval and interaction are more efficient, and semantic robustness is improved under complex working conditions.

The invention discloses a cleaning method and device, a cleaning robot and a readable storage medium, and the method comprises the steps: obtaining a single-frame image, carrying out the recognition of the single-frame image based on a preset deep learning algorithm, and obtaining an initial behavior recognition result; based on a multi-frame image fusion judgment strategy, performing fusion judgment on the initial behavior recognition result corresponding to each single-frame image to obtain a first behavior recognition result; if the first behavior recognition result is abnormal recognition, accumulating each single-frame image, performing time sequence behavior recognition on multiple frames of images obtained by accumulation according to a time sequence behavior recognition algorithm, and determining a second behavior recognition result; determining a target behavior recognition result based on the first behavior recognition result and the second behavior recognition result; the target behavior recognition result is used for determining a target cleaning strategy so as to perform cleaning processing. By adopting the method, the cleaning efficiency is improved.

The application provides a camera calibration method, a calibration device and a system based on a single-frame double calibration board, and relates to the technical field of computer vision. According to third position information and fourth position information of each target feature point on different transparent calibration boards in a camera coordinate system, a space translation vector of a world coordinate system origin and a camera coordinate system origin, a space translation vector of a circle point coordinate system origin and the camera coordinate system origin, an established radial constraint equation and a radial distortion equation, first initial intrinsic parameters and second initial intrinsic parameters of a camera to be calibrated are determined. According to the first initial intrinsic parameters and the second initial intrinsic parameters, final intrinsic parameters of the camera to be calibrated are determined. The application only uses a single-frame image and two parallel calibration boards to realize the calibration of the camera, the calculation amount is small, and the efficiency of the camera calibration is improved.

The embodiment of the invention provides a video intra-frame coding method, a transmission method and related equipment, and belongs to the technical field of data transmission. The method comprises the following steps: performing feature extraction on a coding block of a video frame to obtain a feature vector of the coding block; the feature vector comprises a single-frame content feature and an inter-frame motion feature; weight distribution is carried out on the single-frame content features and the inter-frame motion features according to the network state parameters, feature fusion is carried out on feature vectors according to a weight distribution result, and the importance degree of coding blocks is obtained; dividing the coding block by adopting a corresponding dynamic division strategy according to the importance degree to obtain a division structure of the coding block; and performing intra-frame coding on the coding block according to the division structure, the importance degree and the network state parameter to obtain video coding data. According to the embodiment of the invention, the stability and definition of video transmission can be improved.

The invention relates to the technical field of power distribution automation, and provides a file transmission method suitable for a real-time system and a non-real-time system, which comprises the following steps that: the real-time system acquires a fault signal and triggers a UDP (User Datagram Protocol) to send a task; the real-time system assembles a frame of UDP message according to a UDP message format and information such as a wave recording starting moment, an interval number, a fault sequence number and a data channel number, and sends the frame of UDP message to the non-real-time system; the real-time system splits the recording data in the cache data area into multiple frames of network packets and sends the multiple frames of network packets to a non-real-time system; secondly, according to the timing condition, an ending frame is triggered by fault feature ending and the cycle number; a non-real-time system UDP client task thread receives a first-frame UDP network message, backs up recording related parameter information and stores the recording related parameter information as recording configuration information files such as CFG, HDR and INF; and a non-real-time system UDP client task thread receives the recording data and generates a DAT file. According to the method, real-time system fault triggering and continuous file generation are not influenced.

The invention discloses an inclined sample rapid automatic leveling focusing imaging method based on deep learning, and the method comprises the steps: obtaining a single-frame microscopic image of a sample, dividing the single-frame microscopic image into a plurality of sub-images, and determining a sampling point corresponding to each sub-image and a coordinate of the sampling point in the single-frame microscopic image; inputting each sub-image into a deep learning regression model, and predicting to obtain a defocus distance of each sampling point; according to the coordinate of each sampling point in the single-frame microscopic image and the corresponding defocus distance, calculating to obtain a first compensation inclination angle and a second compensation inclination angle of integral inclination of the surface of the sample; and generating corresponding driving signals to drive the objective table to rotate around the X axis and the Y axis by corresponding angles, so that the surface of the sample is parallel to the focal plane of the microscope. According to the invention, defocus caused by overall inclination of the sample is automatically compensated, and the imaging definition and view field consistency of an uneven or inclined metallographic sample under a microscope are improved.

The utility model discloses a convenient drawer type recycling frame structure based on intelligent recycling machine belongs to environmental protection equipment technical field. The device aims at the problem of existing intelligent recycling machine single frame fixed, manual pulling out laborious, bag taking difficult, door body protruding easy to knock and so on, adopts drawer type structure of recycling frame and door welding, and the door is equipped with hidden handle and foldable lower section, and realizes folding fixed and reset through rebound type door closing hinge, recycling frame bottom is equipped with universal pulley, fixed pulley and fixed scraper, and cooperates with guide groove to realize smooth push and pull and block cleaning, rear lock device can be automatically locked, and support frame structure is welded with scale and realizes accurate weighing. Its advantage lies in: the difficulty of frame body push and pull is greatly reduced, and the problem of taking out full woven bag is solved, the door body folding design avoids knocking and increases the operation space, the automatic reset and locking function improves the operation safety and convenience, effectively prevents the guide groove from being blocked, ensures the long-term stable operation of the equipment, and significantly improves the recycling and cleaning efficiency.

The invention discloses an ultrasonic sound attenuation display method and ultrasonic equipment, and the method comprises the steps: displaying an interface used for selecting a sound attenuation scanning mode, scanning a target tissue based on a first sound attenuation scanning mode in response to a first selection instruction, and obtaining a multi-frame sound attenuation result of a first target region of the target tissue; displaying a multi-frame sound attenuation statistical index of the first target area according to the multi-frame sound attenuation result of the first target area; under the condition that the multi-frame sound attenuation statistical index of the first target area does not meet a first index condition, first abnormity prompting is carried out; in response to the second selection instruction, scanning the target tissue based on a second sound attenuation scanning mode to obtain a single-frame sound attenuation result of a second target area of the target tissue; displaying a single-frame sound attenuation statistical index of the second target area according to the single-frame sound attenuation result of the second target area; and under the condition that the single-frame sound attenuation statistical index of the second target area does not meet a second index condition, carrying out second abnormity prompting.

The invention discloses a living body detection confidence coefficient calculation method based on multi-frame fusion and a dynamic threshold value, and relates to the technical field of identity verification and image processing, and the method comprises the steps: collecting continuous images in a preset time window to obtain an input frame sequence, carrying out the face detection of the input frame sequence, and carrying out the alignment cutting based on face key points, obtaining a human face sub-image sequence and a human face key point sequence; performing quality evaluation on the human face sub-image sequence to generate a frame weight and calculating an overall quality index; calculating a single-frame living body score sequence based on the human face sub-image sequence and the human face key point sequence; carrying out weighted fusion on the single-frame in-vivo score sequence based on the frame weight to obtain in-vivo detection confidence and calculating an inter-frame fluctuation index; and determining a basic threshold value, performing dynamic correction in combination with the overall quality index and the inter-frame fluctuation index to obtain a dynamic threshold value, and comparing the in-vivo detection confidence coefficient with the dynamic threshold value to generate a release or blocking instruction. According to the invention, the stability and cross-scene adaptability of living body determination in a complex environment can be improved.

Referring Video Object Segmentation (RVOS) aims to segment an object referred to by a sentence query throughout an entire video. In contrast to Referring Image Segmentation (RIS), RVOS is particularly faced with dynamic visual challenges, such as position and size variation, pose deformation, object occlusion or exit, and scene variation. Moreover, the referring sentence may contain long-term motions or actions, which may not be easily recognized from a single frame. Existing works that address this challenging task generally require end-to-end training for vision-language models, which can be computationally expensive and time-consuming, while the requirement of dense mask annotations for training impedes the scalability of those approaches. The present disclosure uses grounded prompting to adapt image-based segmentation models to video object segmentation tasks, which can be achieved with relying only on weak supervision.