63 results about "Hand skeleton" patented technology

The invention belongs to the technical field of human-computer interaction, and discloses a digital twin WEB application air gesture interaction method and system. Comprising the following steps: collecting a real-time video stream of a camera of user side equipment, and preprocessing the real-time video stream; x hand region frames are obtained; inputting the X hand region frames into a preset hand key point detection model based on a generative adversarial network to obtain hand key point coordinate data; acquiring a hand skeleton model based on the hand key point coordinate data; acquiring a joint angle and a hand motion track according to the hand skeleton model; mapping the hand skeleton model into a digital twin virtual scene, presetting n gesture instruction modes in the digital twin virtual scene, and matching the hand skeleton model, the joint angle and the hand motion track with the gesture instruction modes; personalized and extensible gesture interaction capability is provided, and man-machine interaction modes are enriched.

The invention provides a self-supervised continuous 3D hand posture tracking method based on a lightweight inertial measurement unit, and the method specifically comprises the following steps: firstly, obtaining a hand motion signal by using a lightweight consumer-level IMU, and extracting features by using a multi-stage neural network containing a bidirectional long-short term memory (Bi-LSTM) module; the global displacement and orientation of the hand are processed through a wrist posture estimation module, and three-dimensional coordinates of hand skeleton points are solved and calculated by means of a finger motion chain; secondly, a self-supervised completion network is realized by combining a random mask and dual loss, and the features are processed to complete complete attitude reconstruction; and finally, combining network output with kinematics prior, generating a three-dimensional grid with reasonable anatomy, solving the problem that joint deformation is inconsistent with torque, and realizing accurate acquisition of a three-dimensional hand posture. For a dynamic hand motion tracking task, the method can adapt to a sparse IMU deployment scene and realize continuous high-precision tracking; the real-time performance demand of daily interaction can be met, and a low-cost solution can be provided for the fields such as medical rehabilitation and virtual interaction which have strict requirements on attitude precision.

System and method for extracting human pose information from an image, comprising a feature extractor connected to a database, a convolutional neural network (CNN) with a plurality of CNN layers. Said system / method further comprising at least one of the following modules: a 2D body skeleton detector for determining 2D body skeleton information from the human-related image features; a body silhouette detector for determining body silhouette information from the human-related image features; a hand silhouette detector for determining hand silhouette detector from the human-related image features; a hand skeleton detector for determining hand skeleton from the human-related image features; a 3D body skeleton detector for determining 3D body skeleton from the human-related image features; and a facial keypoints detector for determining facial keypoints from the human-related image features.

The invention provides a gesture recognition method and system for screen flying interaction, and relates to the technical field of gesture recognition, and the method comprises the steps: processing video data through employing a background subtraction algorithm, and obtaining a foreground region in the video data; extracting a foreground region in the video data by adopting human body posture estimation to obtain a hand key point set of each human body; constructing a hand skeleton model by adopting forward kinematics according to the hand key point set of each human body; utilizing the hand skeleton model to simulate the movement of a hand, and extracting a gesture area and an actual space position of each human body; according to the gesture area and the actual space position of each human body, by combining distance measurement and a collision detection algorithm, whether the gestures of different users are spatially overlapped and crossed or not is judged, the independent gestures and the interactive gestures of the users are distinguished, the problem of misjudgment of a conventional gesture recognition method in the gesture overlapping and crossing state is avoided, and the user experience is improved. Therefore, the accuracy of gesture recognition is improved.

The invention discloses a piano teaching interaction method based on a skeleton point image recognition technology. The method comprises the following steps: S1, collecting video data of hand actions when a user plays a piano; s2, carrying out preprocessing on the video data; s3, extracting hand skeleton point data by using the skeleton point extraction model to obtain a skeleton key point data set; s4, training a hand action recognition network model by using the extracted skeleton key point data set and the loss function; and S5, inputting the real-time output of the skeleton point extraction model into the trained hand action recognition network model, and detecting the correctness of the hand posture. According to the method, the motion information of the hands of the piano player can be captured and analyzed in real time with high precision, and targeted and personalized teaching feedback can be realized through deep mining of skeleton point data, so that the interactivity and teaching efficiency of piano teaching are improved.

The invention discloses a time sequence dynamic gesture recognition method and system. The time sequence dynamic gesture recognition method mainly comprises the steps of S1, hand target detection; step S2, hand target tracking; s3, outputting category information; s4, setting an information container; and S5, gesture motion prediction. According to the method, the problem of time sequence prediction of gesture actions is simplified, meanwhile, the problem of easy ID exchange during target tracking is solved, YOLO is mainly used for detecting a hand and positioning key point information of a hand skeleton, a neural network is realized based on a 1D operator, and gesture action prediction is carried out on time sequence key point information. According to the dynamic gesture recognition method based on combination of the multiple models, lightweight design is carried out on the YOLOv8 model, real-time recognition is achieved on equipment with limited resources (for example, the real-time recognition can reach 25FPS on RK3566), and the problem that ID information is likely to be exchanged when hands are waved crosswise is solved through dynamic threshold control parameters of the target tracking module.

The invention discloses a static sign language recognition method based on skeleton angle features, and belongs to the field of sign language recognition, and the method comprises the steps: obtaining human hand skeleton joint point coordinate data in a historical data set based on a Medipe method; performing data preprocessing on the human hand skeleton joint point coordinate data to obtain a preprocessed data set; constructing a long-short-term memory network model, and training the long-short-term memory network model based on the preprocessed data set to obtain a sign language recognition model; and recognizing the static sign language based on the sign language recognition model. According to the scheme provided by the invention, hand positioning, cutting and hand image adjustment do not need to be carried out, the requirement for a training data set is not higher than that of a traditional scheme, and only a researcher needs to provide a clear hand image.

The invention discloses a humanoid robot arm system and method for a manual treatment integrated training glove, and belongs to the technical field of medical robots. The system comprises a humanoid robot hand, a training glove and intelligent terminal application software. The human-shaped robot hand is made by covering a hand skeleton plate with hydrogel to have the elastic touch feeling and appearance highly imitating the human hand, and touch force monitoring, heating and three-dimensional vibration function modules are integrated in the hand; the training glove is integrated with a finger joint bending degree and pose sensor, can be connected with or separated from the robot arm, and supports combined training and remote control training of the robot arm; and the intelligent terminal application software manages data and is connected with the cloud server. The method comprises the steps of collecting manipulation data of a trainer, driving a robot arm to reproduce manipulation, and generating expert-level treatment data by fusing a cloud expert database or large model optimization. According to the invention, digitalization of expert manipulation treatment, high-precision robot reproduction and intelligent improvement are realized, and the robot is suitable for scenes such as tumor edema, stroke rehabilitation, massage physiotherapy relaxation and the like.

This utility model discloses a handrail frame with steering adjustment function, including a base structure, a rotation adjustment structure installed on the base structure, a mounting block with a connecting rod fixedly mounted on its surface, and a concave cylindrical block fixedly mounted on the top of the mounting block. A limiting hole is formed on the inner side of the concave cylindrical block, and a guide annular groove is formed along the limiting hole inside the concave cylindrical block. The rotation adjustment structure includes a first handrail frame body with a matching rod fixedly mounted at its bottom, and a convex round block fixedly mounted on the surface of the matching rod. A connecting block is fixedly mounted on one side of the first handrail frame body, and another concave cylindrical block is fixedly mounted on the top of the connecting block. The concave cylindrical block is rotatably connected by another matching rod, and the other matching rod is fixedly mounted to the inner side of a second handrail frame body through a U-shaped groove. This handrail frame with steering adjustment function achieves both inner opening and outer fixing through the concave cylindrical block.

The invention relates to the technical field of simulation, in particular to a finger motion trail simulation method and device, equipment, a medium and a program product, and the method comprises the steps: obtaining a hand skeleton image and a hand motion video of a detected target; constructing a three-dimensional hand simulation model according to the hand skeleton image; extracting a plurality of video frames from the hand action video, extracting a two-dimensional coordinate of at least one position point from each of the plurality of video frames, converting the hand action video into a three-dimensional coordinate based on a pre-established coordinate mapping relationship, and forming time sequence data according to the position point of the three-dimensional coordinate; and driving the three-dimensional hand simulation model to execute a simulation action by using the time sequence data, and generating a finger motion track of the tested target according to an execution result of the simulation action. Therefore, the problems of high acquisition cost, poor universality and the like of the finger motion trail in the prior art are solved.

The application provides a hand action interaction rendering method and device, a storage medium and electronic equipment, and applies to the technical field of visual rendering.The target hand model provided by the application is obtained by binding a first hand model and a second hand model on the same hand skeleton hierarchical structure, the geometric size of the second hand model is greater than that of the first hand model, the first hand model is a hand detail model used for hand rendering, and the second hand model is a hand simplified model used for physical interaction collision detection.Collision between the hand simplified model and objects in a virtual environment is detected to determine the mode in which the target hand model is located.In a free space mode, a skeleton pose is calculated by using motion capture data and is synchronized to hand detail model rendering.In a physical interaction mode, a more accurate pose is obtained according to vertex displacement of the hand simplified model and is synchronized to hand detail model rendering, so that penetration of the hand model into virtual objects is effectively prevented, and the authenticity and reliability of hand actions are improved.

The invention relates to a dynamic gesture recognition method based on hand skeleton data, and belongs to the field of medicine, the method comprises the steps of S1, data acquisition and processing, S2, dynamic gesture recognition based on hand skeleton data, S3, C3d model optimization adjustment, C3d model data input size adjustment, and maximum pooling layer addition. The method can better adapt to the recognition requirements of the special gestures of the stroke patient, the size change is matched, and the final feature dimension is not affected. The dynamic gesture recognition based on the hand skeleton data plays a very important role by adjusting the size of the input data, as the features contained in the hand skeleton data are much simpler than those contained in RGB data, the model calculation amount is greatly reduced, and redundant information in the aspects of background, illumination change, hand appearance and the like is also eliminated, so that the dynamic gesture recognition accuracy is greatly improved. And the model can focus on key features more quickly, so that the training time is remarkably shortened.

The application provides an automatic positioning handrail framework welding tool, and relates to the technical field of automobile handrail framework manufacturing. The tool support is provided with an inner table groove in the upper portion, and a transposition servo motor is arranged in the inner table groove. The transposition servo motor is connected with and drives a rotary disc type welding table. Six handrail framework positioning tables are movably arranged on the rotary disc type welding table. A framework rod limiting seat is fixedly connected to the inner end of the upper surface of the handrail framework positioning table. The support rod and the rotary base shell are fixed and properly arranged by the rod body side clamping plate and the round head side clamping plate, respectively. The automatic butt joint, proper arrangement and fixation of the support rod and the rotary base shell are achieved. Manual operation is not needed, time and labor are saved, the problems of low placing efficiency and high deviation rate of manual placing of the handrail framework are solved. After the placing of the handrail framework is completed, the clamping mechanism in the tool is controlled to clamp the handrail framework. The finished product handrail framework after welding and assembly needs to be manually released from clamping and discharged, which is time-consuming and labor-consuming.

The present application provides a gesture tracking method and apparatus, a device, a readable storage medium, and a program product. The method comprises: acquiring a current hand image corresponding to a current user; performing a search to determine whether hand skeleton information corresponding to the current user is stored; and, if it is found that the hand skeleton information corresponding to the current user is stored, determining a hand pose on the basis of the current hand image and the corresponding hand skeleton information. The method of the present application can solve the problem in the existing technology of significant computational resource waste.

The invention discloses a digital opera generation and participation system supporting multi-mode interaction, which comprises an interaction device and a multi-mode interaction subsystem, and is characterized in that the interaction device comprises a shading shell and a conical light outlet which are used for limiting a conical area along a projection direction as a recognizable interaction area; the somatosensory control module is used for collecting hand skeleton and action track information in the recognizable interaction area; the multi-mode interaction subsystem comprises a face recognition module, a digital opera role generation module, an interaction plot control module and a rendering engine execution module. Compared with the prior art, the method has the following advantages: 1, the hand action of the user is accurately captured, the user is allowed to select a plot path, the interactivity and immersion of digital opera exhibition are improved, and the gamification narrative ability of opera is enhanced; and 2, the interaction mode is simple and visual, the system threshold and the use difficulty are reduced, and higher generalizability and universality are achieved.

The application provides a three-dimensional gesture tracking method based on an RGB camera, which comprises the following steps: taking the RGB camera as an input, performing standardization processing on a picture, and sending the picture into a three-dimensional joint detection module to extract image features, predict a preliminary three-dimensional joint and calculate a hand skeleton length; using a particle swarm optimization algorithm to iteratively fit the hand skeleton length and a MAMO hand model, finding an optimal hand shape and obtaining a new three-dimensional joint; sending the new three-dimensional joint into an inverse kinematics module to solve posture parameters required by the MAMO model; using a MANO model to combine the optimal hand shape and the posture parameters θ to obtain final joints and grid vertices; and performing reconstruction rendering on the obtained grid vertices and joints to output a final three-dimensional hand real-time tracking posture. The method provided by the application has high prediction accuracy and high three-dimensional gesture tracking effect precision, and the tracking process and result are easy to realize.

The invention discloses a mixed reality physical entity interaction method and system based on hand skeleton tracking, and belongs to the technical field of human-computer interaction. The problems that in existing mixed reality interaction, in-air gestures are low in precision and prone to fatigue, and a special controller is not portable and high in cost are solved. The method comprises the following steps: acquiring hand three-dimensional skeleton node data when a user grabs a passive physical entity through head-mounted computing equipment; at least two key skeleton nodes are selected, and control parameters representing the real-time relative space relation of the key skeleton nodes are calculated; and establishing mapping between the parameter and the target attribute of the virtual interaction element so as to drive virtual interaction in real time. According to the method, any common physical entity is temporarily converted into a high-precision interaction medium, and the method is mainly used for realizing natural and low-cost fine control with physical feedback in mixed reality application.

A processor identifies keypoints on a hand in a two-dimensional image that is captured by a camera. A three-dimensional pose of the hand is determined using locations of the keypoints to access lookup tables (LUTs) that represent potential poses of the hand as a function of the locations of the keypoints. In some embodiments, the keypoints include locations of tips of fingers and a thumb, joints that connect phalanxes of the fingers and the thumb, palm knuckles that represent a point of attachment of the fingers and the thumb to a palm, and a wrist location that indicates a point of attachment of the hand to a forearm. Some embodiments of the LUTs represent 2D coordinates of the fingers and the thumb in corresponding finger pose planes as a function of the locations of the tips of the fingers or thumb relative to the corresponding palm knuckles.

The invention discloses a multi-sensor hand rehabilitation tracking data glove system and an analysis method, and relates to the technical field of medical rehabilitation instruments and man-machine interaction, and the method comprises the steps: determining the layout position of a sensor according to a hand skeleton anatomical structure, and executing an initial calibration action on a hand; constructing a multi-modal data fusion model according to the attitude data and the bending data, wherein the fusion model comprises a sensor weight relationship in different action modes; inputting the attitude data and the bending data into an anomaly detection model, analyzing the abnormal state of the sensor in real time through a time sequence deep neural network, and outputting an anomaly probability; when it is determined that the sensor is abnormal, using of the data of the abnormal sensor is suspended, and the current hand movement track is reconstructed by adopting the data of another non-abnormal sensor and combining historical data; and driving a virtual hand simulation model according to the fused hand motion angle, reconstructing a hand motion track in real time, and outputting a difference analysis result.

The invention relates to the technical field of motion capture technology, and discloses a human motion capture system based on multi-modal synchronous acquisition, comprising: a motion capture sampling terminal for collecting human motion data including a human motion scene; the optical inertial tactile glove device is used for collecting human hand action data and fingertip tactile data; the time synchronization module generates and outputs a unified synchronous trigger signal; the data processing work station receives, synchronizes and fuses data of the sampling terminal and the optical inertial touch glove device to generate unified whole body and hand skeleton information; the compensation adjustment module is in communication connection with the data processing workstation, receives specified parameters fed back by the data processing workstation, and adjusts the ambient light intensity and the triggering frequency and the triggering time of the synchronous triggering signal based on a preset comparison strategy; the specified parameters comprise an ambient light intensity coefficient, a synchronization rate of whole body and hand skeleton information and actual human body actions, and a movement speed and a movement acceleration of a specified position of a human body.

The invention discloses a hand-containing picture generation method and device, electronic equipment and a storage medium, and the method comprises the steps: generating a first picture based on text information, carrying out hand key point detection processing on the first picture to obtain first skeleton information of a first hand, the first skeleton information is matched with second skeleton information of hand skeletons in a preset skeleton library, a target hand skeleton is determined from the hand skeletons in the preset skeleton library, the target hand skeleton serves as auxiliary guiding information, a second picture is generated based on the text information, and the second picture comprises a second hand. The similarity between the second hand and the first hand meets the preset similarity, and the abnormal rate of the first hand is larger than that of the second hand. According to the embodiment of the invention, the picture is regenerated by using the matched skeleton, so that the possibility of hand malformation is reduced, the consistency of the picture is ensured, and the color and edge problems caused by local generation cannot be caused.

The invention provides a hand action interaction rendering method and device, a storage medium and electronic equipment, and is applied to the technical field of visual rendering. A target hand model provided by the invention is obtained by binding a first hand model and a second hand model on the same hand skeleton hierarchical structure, the geometric size of the second hand model is greater than that of the first hand model, and the first hand model is a hand detail model for hand rendering. The second hand model is a hand simplified model used for physical interaction collision detection. And detecting collision with an object in the virtual environment through the simplified hand model, and judging the mode of the target hand model. In the free space mode, skeleton postures are calculated through motion capture data and synchronized to hand detail model rendering, and in the physical interaction mode, according to vertex displacement of a hand simplified model, more accurate postures are obtained and synchronized to hand detail model rendering, so that the hand model is effectively prevented from penetrating through a virtual object, and the user experience is improved. And the authenticity and reliability of hand actions are improved.

The application discloses a kind of intelligent animation modeling methods based on three-dimensional technology, it is related to computer graphics and three-dimensional animation production technical field, the application reconstructs hand-object interaction logic by three-dimensional technology, realize natural fine motion generation;In virtual anchor end, such as coffee cup scene, the spatial relationship of hand skeleton and prop point cloud is quantified as the topological connection diagram that can be calculated, rigid connection edge ensures the stable grip of functional area, fingertip and cup body have no suspended gap;Elastic adsorption edge allows flexible contact of non-functional area, when palm pressure changes, deformation gradient field drives prop surface microdeformation, synchronous joint torque dynamic adjustment, avoid hand rigid distortion when coffee pours in traditional scheme. The collaborative design of graph convolution network and physical engine further eliminates the risk of wearing mold: equidistance constraint of prop rigid area retains original topological structure, and soft contact area absorbs collision energy through deformation gradient field.

The present application relates to a kind of handrail framework assembly welding fixture, including the A clamping unit for the clamping of slide rail support sheet metal part, the B clamping unit for the clamping of left handrail vertical support piece and right handrail vertical support piece, the C clamping unit for the clamping of handrail horizontal support square steel, handrail vertical support square steel, outer handrail connecting plate, left handrail vertical fixed square steel, the D clamping unit for the clamping of lower end framework connecting plate, the E clamping unit for the clamping of right handrail vertical fixed square steel, the F clamping unit for the clamping of outer plate fixed support steel wire, the G clamping unit for the clamping of lower end framework connecting steel wire, the H clamping unit for the clamping of handrail support steel wire.The above scheme provided by the present application can effectively clamp and position each component of handrail framework assembly reliably, so as to reliably weld and connect each component on the welding fixture, improve welding efficiency and reduce labor intensity.

The invention belongs to the technical field of virtual reality and simulation, and relates to a virtual hand construction model based on three-dimensional space scanning and a rapid construction method.The model comprises a real hand data extraction module, a 3D collector is used for conducting accurate scanning on the hand of the human body, the collected information generates hand point, line and surface in software, and the hand point, line and surface is obtained; grid editing and material generation are carried out through the point cloud, and acquisition and generation of a real hand model are realized; the virtual hand skeleton definition module is used for building a skeleton for the model according to a real skeleton structure, and sequentially carrying out weight setting on each joint, so that the virtual hand skeleton is associated with the real hand model, and the real hand model is driven by the skeleton to carry out action definition; and the virtual hand rapid packaging integration module is used for carrying out motion relation constraint binding on virtual hand bones, so that application of a data glove and a real hand model in a VR cabin design control simulation scene is realized, and the bound real hand model needs to be synchronously operated by an operator wearing the data glove. The data glove controls the real hand model to execute hand opening and fist clenching actions, the actions are completely smooth, and packaging of the virtual hand model is completed; according to the interaction application module, in a VR cabin design control simulation scene, the virtual hand model can perform grabbing, pushing, pulling, stirring and rotating actions on an accelerator table, an operation rod, a stirring button and a knob model in a cabin.

The application discloses a kind of based on semi-supervised 3D skeleton estimation method, device, equipment and storage medium, it includes: obtaining to be processed image, the human skeleton or hand skeleton is included in the to-be-processed image;The to-be-processed image is input into skeleton estimation model, obtains the target three-dimensional skeleton coordinates corresponding to the human skeleton or the hand skeleton, wherein the skeleton estimation model includes by extracting features to training image data, the skeleton point uvd coordinate, the skeleton point space coordinate and the hidden variable camera mapping image parameter obtained are trained neural network by preset loss function, the skeleton point uvd coordinate includes the image coordinate of skeleton point and the depth value corresponding to the image coordinate of skeleton point.It can meet the use demand of user, while, greatly save the cost of 3D skeleton data acquisition and annotation.

The invention is suitable for the technical field of terminals, and provides an air gesture recognition method, electronic equipment and a computer program product. And inputting the hand shape categories, the hand skeleton point information and the joint distance vectors corresponding to the M frames of target images including the continuous N frames of target images into a dynamic gesture recognition model for processing to obtain confidence vectors of the air gestures, and determining the categories of the air gestures according to the confidence vectors. The dynamic gesture recognition model is obtained by training a large amount of different sample data, so that the air gesture recognition method can have relatively high generalization performance when the dynamic gesture recognition model is adopted to recognize the air gesture category; the method can cope with various air-crossing gestures with different hand shape change characteristics made by different users for the same air-crossing gesture, and the use experience of the air-crossing gesture function is improved.

The application relates to the technical field of motion capture technology and discloses a human motion capture system based on multi-modal synchronous acquisition, which comprises a motion capture sampling terminal, which collects human motion data containing a human motion scene; an optical-inertial-tactile glove device, which collects human hand motion data and fingertip tactile data; a time synchronization module, which generates and outputs a unified synchronous trigger signal; a data processing workstation, which receives, synchronizes and fuses data from the motion capture sampling terminal and the optical-inertial-tactile glove device, and generates unified whole-body and hand skeleton information; and a compensation adjustment module, which is in communication connection with the data processing workstation, receives specified parameters fed back by the data processing workstation, adjusts the environmental light intensity and the trigger frequency and trigger time of the synchronous trigger signal based on a preset comparison strategy; the specified parameters include an environmental light intensity coefficient, a synchronization rate of the whole-body and hand skeleton information and actual human motion, and motion speed and motion acceleration of a specified position of the human body.

The invention provides a method, a device and equipment for automatically binding a target 3D object and a digital human hand. The method comprises the following steps: determining a hand skeleton of a preset digital human and a target 3D object to be bound with the hand skeleton; based on the geometric features of the target 3D object, determining a target gesture required by the hand skeleton to hold the target 3D object; determining the current pose information of the target 3D object, and determining the current reference position of the hand skeleton; based on the current pose information of the target 3D object and the current reference position of the hand skeleton, determining displacement information of the target 3D object moving to the reference position; according to the target gesture, generating a hand closing simulation track of the hand joint; and based on the hand closed simulation trajectory, performing collision detection on each hand joint in the hand skeleton to obtain a relative position relationship between each hand joint in the hand skeleton and the target 3D object when the hand skeleton holds the target 3D object with the target gesture.

The application discloses an immersion interactive method and device for appreciating artifacts, and relates to the technical field of human-computer interaction. The method comprises the following steps: in an immersive digital experience cabin, the three-dimensional coordinates of the user's double pupils and the hand skeleton node coordinates are collected, the gesture instruction is analyzed, and the three-dimensional space viewpoint parameter set of the next moment is predicted; in a virtual engine scene, the UV texture coordinates are obtained by ray intersection, the three-dimensional region of interest is demarcated, the candidate tile set and the tile topology feature matrix are retrieved and generated; based on the pre-constructed fitness function, the improved tornado optimization algorithm is used for solving, and the global optimal tile loading sequence is output; the naked-eye light field rendering and the three-dimensional space multi-modal superposition are performed on the global optimal tile loading sequence, and the fusion picture of the artifacts and the suspended interpretation is presented on the naked-eye 3D cabin screen. The application solves the problems of viewpoint prediction lag, texture tile loading leading to video memory overflow or picture damage, and lack of spatial multi-modal fusion in the prior art.