Production method of large-scale group intelligent sports in movie and television animation production

Abstract

The invention relates to the technical field of movie and television animation production, in particular to a production method of large-scale group intelligent sports in movie and television animation production. Comprising the following steps: creating any manufacturing surface, and obtaining individual attributes of each individual in an initial frame; predicting the update frame, and obtaining the operation position of each individual; performing collision detection on each individual according to the obtained running position and individual attribute of each individual; according to the collision detection result between the individuals, adjusting the individual attributes of the individuals according to an avoidance strategy; the frames are updated, the continuous operation positions of all the individuals are obtained, and continuous movie and television animations of group movement are formed; according to the method, the positions of the individuals are predicted in advance in combination with the constant-speed and accelerated motion conditions of the individuals, collision detection is carried out, and then different avoidance strategies are adopted, so that the individuals in the group are prevented from colliding in subsequent operation, and automatic generation of the large-scale group intelligent motion animation is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of film and television animation production, and in particular to a production method of large-scale group intelligent motion in film and television animation production. Background Art

[0002] Film and television animation refers to animated films, and film and television 3D animation involves film and television special effects creativity, pre-shooting, film and television 3D animation, special effects post-synthesis, film and television special effects animation, etc.

[0003] In the history of film and television animation production, manual drawing is the main way to construct group motion animation. Animators rely on their own artistic creativity and understanding of the laws of motion to draw the posture and position changes of each individual in the group frame by frame. However, once faced with a large-scale group scene, their workload increases greatly. With the application of computer technology in the field of animation production, graphic drawing and transformation tools have begun to appear, which enables animation production to improve efficiency to a certain extent with the help of computer computing power, but this method lacks in-depth simulation of individual behavior.

[0004] The patent document with application number "CN201110447842.8" records that "it includes the following steps: creating a production surface; dividing the production surface into several small production surfaces; creating a particle emitter on the production surface to generate particles, each particle represents an individual in the group; the small production surface is the emission area of ​​the particles, and the particles appear in this area according to the set parameters; setting the movement behavior of the particles, and the particles move on the production surface according to the set movement behavior; setting the particle intelligent avoidance mode, when the particles are not blocked within a certain range, the particles move along the established behavior, and when the particles are blocked within a certain range, the above particles each rotate in a certain direction and move; randomly replacing the particles into a cyclic motion of group motion". This patent provides a method for producing large-scale group motion, which forms a cyclic animation of group motion by emitting particles and moving the particles on the production surface according to the set movement behavior. It lacks consideration of the different attributes of individuals and reasonable prediction and adjustment of individual motion, and cannot meet the use requirements.

[0005] Based on this, the present invention provides a method for producing large-scale group intelligent motion in film and television animation production to solve the technical problems raised above. Summary of the invention

[0006] The purpose of the present invention is to provide a method for producing large-scale group intelligent motion in film and television animation production, which comprehensively considers the various attributes of individuals, combines uniform and accelerated motion conditions, predicts individual positions in advance, performs collision detection in real time based on the predicted running positions and attributes of the individuals, and adopts different avoidance strategies to avoid collisions between individuals in the group in subsequent operations, thereby realizing the automatic generation of large-scale group intelligent motion animations, thereby greatly reducing manual workload and improving production efficiency.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] The present invention provides a method for producing large-scale group intelligent motion in film and television animation production, comprising the following steps:

[0009] Create any production surface and obtain the individual properties of each body in the initial frame;

[0010] Predict the update frame and obtain the running position of each individual;

[0011] According to the acquired running positions and individual properties of each individual, collision detection is performed on each individual;

[0012] According to the collision detection results between individuals, the individual attributes of the individuals are adjusted according to the avoidance strategy;

[0013] Update frames to obtain the continuous running positions of each individual, forming a continuous video animation of group movement.

[0014] The present invention is further configured as follows: the individual attributes include position, mass, individual radius, speed, acceleration and perception radius.

[0015] The present invention is further configured as follows: obtaining the running position of each individual includes:

[0016] Uniform motion position: r a (t+Δt)==r a (t)+v a Δt, where r a (t) is the current position of individual a, v a is the speed of individual a, Δt is the time interval for updating frames;

[0017] Acceleration position: In the formula, a a is the acceleration of individual a.

[0018] The present invention is further configured as follows: the process of performing collision detection on each individual is as follows:

[0019] Obtain the set of individuals within the perception radius of each individual in the predicted update frame;

[0020] According to the judgment rules, determine whether any two individuals in the individual set collide.

[0021] The present invention is further configured as follows: the determination rule is: assuming that the position of individual a is (x a ,y a 、z a ), the position of individual b is (x b ,y b 、z b ), the individual radius of individual a is r a , the individual radius of individual b is r b ,like It is determined that individual a and individual b collide; otherwise, individual a and individual b do not collide.

[0022] The present invention is further configured as follows: the avoidance strategy includes the following contents:

[0023] When a collision is predicted, if the distance between individual a and individual b is less than a preset threshold, the vehicle will turn to avoid the collision.

[0024] Otherwise, adjust the speed to avoid the situation;

[0025] When no collision is predicted, the individual attributes of the individuals are not adjusted.

[0026] The present invention is further configured as follows: the process of steering avoidance is as follows:

[0027] Calculate the potential collision individual a(x a ,y a 、z a ) relative to the current individual b(x b ,y b 、z b )'s position vector

[0028] Calculate the normal vector of the turning plane of individual a In the formula, is the current motion direction vector;

[0029] The individual a Rotation αθ max Angle, get the direction vector after turning Among them, α is the steering coefficient, θ max is the maximum turning angle of individual a;

[0030] Update the movement direction vector of individual a to

[0031] The present invention is further configured as follows: the process of speed adjustment avoidance is as follows:

[0032] Calculate the relative speed v between individual a and potential collision individual b ab and the current relative distance d ab ;

[0033] According to the relative speed v ab and distance d ab , calculate the collision time

[0034] Calculate the preparatory adjustment speed of individual a In the formula, v a is the current movement speed of individual a, β is the adjustment coefficient, m a is the mass of individual a, m b is the mass of individual b;

[0035] If |v a -v a ′|>a max t ab , where a max is the maximum acceleration of individual a, then change β to satisfy |v a -v a ′|≤a max t ab ;

[0036] Adjust the speed of individual a to satisfy |v a -v a ′|≤a max t ab V a ′.

[0037] The present invention is further configured to render each individual according to the importance of each individual in the group.

[0038] Compared with the prior art, the present invention has the following beneficial effects:

[0039] The present invention creates an arbitrary production surface, obtains the individual attributes of each individual in the initial frame, predicts and updates the frame, obtains the running position of each individual, performs collision detection on each individual according to the running position and individual attributes of each individual, and then adjusts the individual attributes of the individual according to the avoidance strategy according to the collision detection result between individuals, and finally updates the frame to obtain the continuous running position of each individual, so as to form a continuous film and television animation of group movement. The production method of large-scale group intelligent movement in film and television animation production provided by the present invention comprehensively considers the various attributes of individuals, can reflect the unique physical characteristics and behavioral tendencies of each individual in the group, combines the uniform and accelerated motion conditions, predicts the individual position in advance, performs collision detection in real time based on the predicted running position and attributes of the individual, and adopts different avoidance strategies according to different situations, adjusts the attributes of the individual, avoids collisions between individuals in the group in subsequent operation, forms a continuous film and television animation of group movement by cyclically updating frames and integrating the continuous running positions of individuals, and realizes the automatic generation of large-scale group intelligent movement animation, thereby greatly reducing the manual workload and improving the production efficiency, and is particularly suitable for animation production of long-term and large-scale group movement. DETAILED DESCRIPTION

[0040] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] Example:

[0042] This embodiment provides a method for producing large-scale group intelligent motion in film and television animation production, including the following steps:

[0043] S1. Create an arbitrary production surface and obtain the individual attributes of each individual in the initial frame.

[0044] Furthermore, individual attributes include position, mass, individual radius, velocity, acceleration, and perception radius.

[0045] In this embodiment, it should be noted that by creating a production surface and obtaining the initial attributes of individuals, a basic environment can be built for subsequent group motion simulation, and the key parameters of each individual's starting state can be clarified. By creating any suitable production surface, spatial scenes of different scenes can be constructed, and the individual attributes of each individual in the initial frame can be obtained, covering position (determining the initial coordinates of the individual in space), mass (affecting the collision effect), individual radius (used for collision detection and judgment), speed (initial movement speed), acceleration (change in movement speed) and perception radius (determining the range of the individual's ability to perceive other individuals around).

[0046] S2. Predict and update the frame to obtain the running position of each individual.

[0047] Furthermore, obtaining the running position of each individual includes:

[0048] Uniform motion position: r a (t+Δt)==r a (t)+v a Δt, where r a (t) is the current position of individual a, v a is the speed of individual a, Δt is the time interval for updating frames;

[0049] Acceleration position: In the formula, a a is the acceleration of individual a.

[0050] In this embodiment, it should be noted that the position of the individual in the subsequent update frame is estimated so as to know the individual movement trend in advance and prepare for collision detection. As a real-time method, when the individual moves at a constant speed, assuming that an individual is currently at the coordinates (1, 2, 3) and the speed is (0.5, 0, 0), then in the next frame, its position in the x-axis direction will move to 1+0.5×1=1.5, the y-axis and z-axis coordinates remain unchanged, and the updated position is (1.5, 2, 3); for example, in a racing game animation scene, the vehicle individuals have different initial speeds and accelerations. For a vehicle with an initial speed of 10m / s and an acceleration of 2m / s 2 The time interval is 1s. Assuming the initial position is (0, 0, 0), the accelerated motion position in the x-axis direction is 11. This embodiment takes into account both uniform and accelerated motion conditions, and can simulate more diverse individual motion patterns, which is suitable for various group scenes with different motion characteristics. The accurate position prediction provides an accurate data basis for subsequent collision detection, and improves the reliability and stability of the entire group motion simulation.

[0051] S3. Perform collision detection on each individual according to the acquired running position and individual attributes of each individual.

[0052] Furthermore, the process of collision detection for each individual is as follows:

[0053] Obtain the set of individuals within the perception radius of each individual in the predicted update frame;

[0054] According to the judgment rules, determine whether any two individuals in the individual set collide.

[0055] Furthermore, the decision rule is: Assume that the position of individual a is (x a ,y a 、z a ), the position of individual b is (x b ,y b 、z b ), the individual radius of individual a is r a , the individual radius of individual b is r b ,like It is determined that individual a and individual b collide; otherwise, individual a and individual b do not collide.

[0056] In this embodiment, it should be noted that detecting whether collisions will occur between individuals in a group is an important link to ensure the rationality and authenticity of group movement. By predicting and discovering potential collisions, subsequent avoidance strategies can be triggered to avoid animation effects that do not conform to realistic logic, such as individual overlap or crossing, making group movement more natural and smooth. The present invention performs collision detection based on individual running positions and attributes, taking into account the dynamic changes of individuals during movement, and can adapt to the situation where individuals constantly change their positions and states during group movement. In addition, by obtaining a set of individuals within the perception radius and then performing collision detection, unnecessary collision calculations are effectively reduced, and the efficiency of collision detection is improved. Especially in large-scale group scenes, the speed and performance of the overall simulation can be significantly improved; by timely discovering potential collisions, subsequent avoidance strategies can be triggered to avoid animation effects that do not conform to realistic logic, such as individual overlap or crossing, making group movement more natural and smooth.

[0057] S4. According to the collision detection results between individuals, the individual attributes of the individuals are adjusted according to the avoidance strategy.

[0058] Furthermore, the avoidance strategy includes the following:

[0059] When a collision is predicted, if the distance between individual a and individual b is less than a preset threshold, the vehicle will turn to avoid the collision.

[0060] Otherwise, adjust the speed to avoid the situation;

[0061] When no collision is predicted, the individual attributes of the individuals are not adjusted.

[0062] The process of steering avoidance is as follows:

[0063] Calculate the potential collision individual a(x a ,y a 、z a ) relative to the current individual b(x b ,y b 、z b )'s position vector

[0064] Calculate the normal vector of the turning plane of individual a In the formula, is the current motion direction vector;

[0065] The individual a Rotation αθ max Angle, get the direction vector after turning Among them, α is the steering coefficient, θ max is the maximum turning angle of individual a;

[0066] Update the movement direction vector of individual a to

[0067] The process of speed adjustment avoidance is as follows:

[0068] Calculate the relative speed v between individual a and potential collision individual b ab and the current relative distance d ab ;

[0069] According to the relative speed v ab and distance d ab , calculate the collision time

[0070] Calculate the preparatory adjustment speed of individual a In the formula, v a is the current movement speed of individual a, β is the adjustment coefficient, m a is the mass of individual a, m b is the mass of individual b;

[0071] If |v a -v a ′|>a max t ab , where a max is the maximum acceleration of individual a, then change β to satisfy |v a -v a ′|≤a max t ab ;

[0072] Adjust the speed of individual a to satisfy |v a -v a ′|≤amax t ab V a ′.

[0073] In this embodiment, it should be noted that when collision detection finds potential collision risks, by adjusting the attributes of individuals, the actual occurrence of collisions can be effectively avoided, ensuring that group movement can continue and making group movement appear intelligent and orderly. The present invention provides two different avoidance strategies, which can be flexibly selected according to the specific circumstances of the collision, so that the group can make more reasonable and diversified responses when facing different collision risks, thereby increasing the intelligence and authenticity of group motion simulation; in addition, the present invention takes into account multiple attributes of individuals and relative motion relationships in the avoidance strategy, and determines the adjustment amount through precise calculation. Compared with the simple fixed rule avoidance method, the present invention can better simulate the avoidance behavior that conforms to the laws of physics, and is more natural and realistic in visual effect. As an implementation method, assuming that the mass of individual a is 100 and the speed is (2, 0, 0), the mass of individual b is 80 and the speed is (1.5, 0, 0), the calculated relative speed is (0.5, 0, 0), and the relative distance is assumed to be 1, then the collision time is 2, if the adjustment coefficient is 0.8, then the prepared adjustment speed is (1.6, 0, 0), if the maximum acceleration of individual a is 0.5 and the time interval is 1, then 0.4<0.5, which meets the requirements, and the speed can be updated to (1.6, 0, 0).

[0074] S5. Update the frames, obtain the continuous running positions of each individual, and form a continuous video animation of group movement.

[0075] In addition, it also includes rendering each individual according to its importance in the group.

[0076] In this embodiment, it should be noted that this embodiment obtains the position change of individuals in a continuous time sequence (i.e., multiple update frames) by continuously repeating the previous steps of predicted position, collision detection, and avoidance strategy adjustment. By integrating these position information, continuous video animation of group movement can be generated, so that the group movement gradually evolves from a static initial state to a dynamic, coherent animation sequence, completing the production of large-scale group intelligent movement in the entire film and television animation production; the present invention adopts a cyclic update frame method to realize the intelligent continuous simulation of group movement, thereby greatly improving the production efficiency, and is particularly suitable for the animation production of a large number of individuals in a large-scale group scene for a long time. At the same time, due to the accurate simulation of individual movement and interaction in the previous steps, the continuous animation formed has a higher quality in the overall visual effect of group movement. In addition, while generating high-quality film and television animation, the rendering resources are reasonably allocated to achieve the best balance between visual presentation and production efficiency. As an implementation method, in the animation production of an elephant migration, firstly, the initial attributes of many individual elephants are set in the initial frame and their positions in the starting habitat are determined. Then, in each update frame, the position of each elephant is predicted, collisions between elephants are detected, and avoidance adjustments are made according to the above steps. With the update of each frame, the position of each elephant is constantly changing, and they form various formations to migrate, etc., finally forming a complete continuous animation of elephant migration, showing the entire migration process from the departure point to the destination.

[0077] The method for producing large-scale group intelligent motion in film and television animation production provided by the present invention creates an arbitrary production surface, obtains the individual attributes of each individual in the initial frame, predicts and updates the frame, obtains the running position of each individual, performs collision detection on each individual according to the running position and individual attributes of each individual obtained, and then adjusts the individual attributes of the individual according to the avoidance strategy according to the collision detection result between the individuals, and finally updates the frame to obtain the continuous running position of each individual, so as to form a continuous film and television animation of group motion; the present invention comprehensively considers multiple attributes of individuals, can reflect the unique physical characteristics and behavioral tendencies of each individual in the group, combines the uniform speed and accelerated motion conditions, predicts the individual position in advance, performs collision detection in real time based on the predicted running position and attributes of the individual, and adopts different avoidance strategies according to different situations to adjust the attributes of the individual, so as to avoid collisions between individuals in the group in subsequent operations, and forms a continuous film and television animation of group motion by cyclically updating frames and integrating the continuous running positions of individuals, thereby realizing the automatic generation of large-scale group intelligent motion animation, thereby greatly reducing the manual workload and improving the production efficiency, and is particularly suitable for animation production of long-term and large-scale group motion.

[0078] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0079] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A method for producing large-scale group intelligent motion in film and television animation production, characterized in that: The following steps are involved: Create any production surface and obtain the individual properties of each body in the initial frame; Predict the update frame and obtain the running position of each individual; According to the acquired running positions and individual properties of each individual, collision detection is performed on each individual; According to the collision detection results between individuals, the individual attributes of the individuals are adjusted according to the avoidance strategy; Update frames to obtain the continuous running positions of each individual, forming a continuous video animation of group movement.

2. A method for producing large-scale group intelligent motion in film and television animation production according to claim 1, characterized in that: The individual attributes include position, mass, individual radius, speed, acceleration and perception radius.

3. The method for producing large-scale group intelligent motion in film and television animation production according to claim 1, characterized in that: The obtaining of the running position of each individual comprises: Uniform motion position: r a (t+Δt)==r a (t)+v a Δt, where r a (t) is the current position of individual a, v a is the speed of individual a, Δt is the time interval for updating frames; Acceleration position: In the formula, a a is the acceleration of individual a.

4. The method for producing large-scale group intelligent motion in film and television animation production according to claim 1, characterized in that: The process of performing collision detection on each entity is as follows: Obtain the set of individuals within the perception radius of each individual in the predicted update frame; According to the judgment rules, determine whether any two individuals in the individual set collide.

5. The method for producing large-scale group intelligent motion in film and television animation production according to claim 4, characterized in that: The determination rule is: Assume that the position of individual a is (x a ,y a 、z a ), the position of individual b is (x b ,y b 、z b ), the individual radius of individual a is r a , the individual radius of individual b is r b ,like It is determined that individual a and individual b collide; otherwise, individual a and individual b do not collide.

6. The method for producing large-scale group intelligent motion in film and television animation production according to claim 1, characterized in that: The avoidance strategy includes the following: When a collision is predicted, if the distance between individual a and individual b is less than a preset threshold, the vehicle will turn to avoid the collision. Otherwise, adjust the speed to avoid the situation; When no collision is predicted, the individual attributes of the individuals are not adjusted.

7. A method for producing large-scale group intelligent motion in film and television animation production according to claim 6, characterized in that: The process of steering avoidance is as follows: Calculate the potential collision individual a(x a ,y a 、z a ) relative to the current individual b(x b ,y b 、z b )'s position vector Calculate the normal vector of the turning plane of individual a In the formula, is the current motion direction vector; The individual a Rotation αθ max Angle, get the direction vector after turning Among them, α is the steering coefficient, θ max is the maximum turning angle of individual a; Update the movement direction vector of individual a to 8. The method for producing large-scale group intelligent motion in film and television animation production according to claim 6, characterized in that: The process of speed adjustment avoidance is as follows: Calculate the relative speed v between individual a and potential collision individual b ab and the current relative distance d ab ; According to the relative speed v ab and distance d ab , calculate the collision time Calculate the preparatory adjustment speed of individual a In the formula, v a is the current movement speed of individual a, β is the adjustment coefficient, m a is the mass of individual a, m b is the mass of individual b; If |v a -v a ′|>a max t ab , where a max is the maximum acceleration of individual a, then change β to satisfy |v a -v a ′|≤a max t ab ; Adjust the speed of individual a to satisfy |v a -v a ′|≤a max t ab V a ′.

9. The method for producing large-scale group intelligent motion in film and television animation production according to claim 1, characterized in that: It also includes rendering each individual according to their importance in the group.

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