Animation image management system and method based on multi-source data

Abstract

The present invention relates to the field of animation image management technology, and specifically to an animation image management system and method based on multi-source data. The present invention monitors the input operations of users with corresponding authority in each animation production area of ​​an animation production platform, comprehensively compares the deviations of animation effect images presented in the corresponding animation production area after each input operation, and extracts the effective process nodes generated in each animation production area according to the result of the comprehensive comparison. Then, by evaluating the efficiency value of each effective process node and sorting out the changing trend of the efficiency value, an early warning prompt is provided for the slow progress of animation production work carried out in each animation production area, thereby realizing efficient supervision of the animation production platform.

Description

Technical Field

[0001] The present invention relates to the technical field of animation image management, and in particular to an animation image management system and method based on multi-source data. Background Art

[0002] The product animation collaboration model refers to the way in which different departments or teams work together to complete product animation. This model usually includes the following three main steps: 1. Planning stage: In this stage, the team will determine the goals and objectives of the product animation and plan the process to achieve these goals. This may include developing a project schedule, determining the required resources, and determining the responsibilities and roles of the participating team members. 2. Production stage: In this stage, the team begins to produce animations, which usually involves the cooperation of multiple departments, such as design, animation, sound effects, programming, etc. This stage requires strict collaboration and communication to ensure smooth coordination of team members. 3. Release stage: In this stage, the team will test and review the product animation. If improvements are needed, the team will make modifications and retest until the final version is released. The advantage of the product animation collaboration model is that it can speed up project progress, improve efficiency, and ensure close cooperation between various teams. At the same time, this model can reduce the risk of misunderstandings and communication barriers, and ultimately achieve high-quality product animations.

[0003] Animation production is a complex task that requires teamwork and a sophisticated production process. During the animation production process, delays in production progress are a common problem. This may be because a problem occurred in a certain link in the production process, which affected the overall progress. It is necessary to eliminate and discover the cause of the delay in a timely manner, and take corresponding measures to speed up the production progress; Regarding the collaborative production management of animation, the Chinese patent with publication number CN117710534A and the name of the collaborative animation production method based on improved teaching and learning optimization algorithm discloses a technical effect of collaboratively distributing content in the animation production process to achieve collaborative animation modeling, ensure computer data processing advantages, and thereby improve animation production efficiency and production quality effects, but does not involve the process supervision issue in the collaborative animation production process. Summary of the invention

[0004] The object of the present invention is to provide an animation image management system and method based on multi-source data to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: an animation image management method based on multi-source data, the method comprising:

[0006] Step S1: in the animation production platform, in accordance with the production content of the target animation, input operations entered by the authorized account with corresponding production authority are captured and numbered in sequence, and the animation effect images presented in the corresponding animation production area after each input operation is entered are extracted in sequence;

[0007] Step S2: establishing an association tag between each input operation and the corresponding animation effect image; intercepting the production process node in each animation production area; adjusting the interception process of the production process node according to the presentation change of the animation effect image caused by the corresponding production process node in each animation production area, and identifying and extracting the valid process node;

[0008] Step S3: Calculate the corresponding efficiency value for each valid process node according to the presentation change of the animation effect image caused by each interval input operation in each valid process node;

[0009] Step S4: setting a unit monitoring period, performing curve fitting on the efficiency values ​​of all valid process nodes extracted from each animation production area in the current unit monitoring period, and obtaining an efficiency value change curve corresponding to each animation production area in the current unit monitoring period;

[0010] Step S5: According to the efficiency value change curve, monitor the progress change of each animation production area within each unit monitoring cycle, and provide early warning feedback to the management personnel based on the monitoring results.

[0011] Preferably, step S2 comprises:

[0012] Step S2-1: Assume that a production process node includes N input operations, where N ≥ 3. Whenever N input operations are captured sequentially in an arbitrary animation production area, a production process node corresponding to the arbitrary animation production area is constructed and generated; and according to the associated labels, corresponding animation effect images are extracted for each input operation constituting each production process node;

[0013] Step S2-2: in the generated production process node, the image similarity between the animation effect images corresponding to every two adjacent input operations is obtained in sequence; by default, the animation effect image corresponding to the first input operation in the generated production process node is used as the base reference image, and the image similarity between the animation effect image corresponding to each input operation starting from the second input operation and the base reference image is obtained in sequence;

[0014] Step S2-3: If P(S 1 ,S 2 )>P(S 1,S 3 )>...>P(S 1 ,S N ), the generated production process node is determined as a valid process node, where P(S 1 ,S 2 )、P(S 1 ,S 3 ), ..., P(S 1 ,S N ) respectively represent the image similarities between the animation effect images corresponding to the 2nd, 3rd, ..., Nth input operations in a certain production process node and the benchmark reference image;

[0015] When P(S 1 ,S 2 )>P(S 1 ,S 3 )>...>P(S 1 ,S N ), it indicates that the first input operation is performed to present the animation effect image S 1 On the basis of, the changes caused by the second input operation to the animation effect image presented in the corresponding animation production area from the second input operation to the Nth input operation are gradually increased, and the animation effect image presented in the corresponding animation production area is objectively changed from the second input operation to the Nth input operation;

[0016] Step S2-4: If the image similarity P(S 1 ,S k ) satisfies P(S 1 ,S k-1 ) <P(S 1 ,S k ), where 2≦k≦N, P(S 1 ,S k-1 ) represents the image similarity between the animation effect image corresponding to the k-1th input operation and the baseline reference image, removes the kth input operation from the generated production process node, triggers the input operation to be added in sequence, and generates a new production process node until the new production process node is determined to be a valid process node.

[0017] Preferably, step S3 includes:

[0018] Step S3-1: extract each valid process node determined from each animation production area; obtain the total time T from capturing the first input operation to capturing the Nth input operation in each valid process node;

[0019] Step S3-2: Calculate the corresponding efficiency value β for each valid process node:

[0020] β=1 / [P(S 1 ,S 2 )+P(S 2 ,S 3 )]+...+P(S N-1 ,S N )] / (N-1)+1 / P(S 1 ,S N ) / T;

[0021] Among them, P(S 1 ,S 2 )、P(S 2 ,S 3 ), ..., P(S N-1 ,S N ) are respectively the image similarity between the animation effect image corresponding to the first input operation and the animation effect image corresponding to the second input operation, and the image similarity P(S) between the animation effect image corresponding to the second input operation and the animation effect image corresponding to the third input operation in each valid process node. 2 ,S 3 ), ..., the image similarity between the animation effect image corresponding to the Nth input operation and the animation effect image corresponding to the N-1th input operation; where P(S 1 ,S N ) represents the image similarity between the animation effect image corresponding to the 1st input operation and the animation effect image corresponding to the Nth input operation in each valid process node;

[0022] Among them, P(S 1 ,S N ) / T, the larger the value, the greater the 1 ,S N The smaller the value of [P(S ) / T is, the smaller the rate of change in the process of causing the difference between the animation effect image corresponding to the first input operation and the animation effect image corresponding to the Nth input operation in the valid process node is; 1 ,S 2 )+P(S 2 ,S 3 )]+...+P(S N-1 ,S N )] / (N-1) represents the average image similarity between the animation effect images corresponding to all two adjacent input operations in the valid process node.

[0023] Preferably, step S4 includes: sequentially numbering all valid process nodes extracted from each animation production area within the current unit monitoring period, and extracting the efficiency value corresponding to each valid process node; for each animation production area, taking the serial number corresponding to each valid process node extracted within the current unit monitoring period as x, and the efficiency value corresponding to each valid process node as y, curve fitting is performed to obtain the efficiency value change curve y=Fx+b corresponding to each animation production area, wherein F represents the slope and b is a constant.

[0024] Preferably, step S5 comprises:

[0025] Step S5-1: If the slope of the efficiency value variation curve presented by a certain animation production area in the current unit monitoring period is F<0, and |F|>η, where η represents a threshold, a warning mark is made for the certain animation production area;

[0026] Step S5-2: Assume that the total number of valid process nodes captured for a certain animation production area in the current unit monitoring cycle is Q. When the first valid process node generated in the next unit monitoring cycle is extracted for a certain animation production area, input x=Q+1 into the efficiency value change curve constructed for the certain animation production area in the current unit monitoring cycle to obtain the efficiency prediction value. At the same time, obtain the efficiency value corresponding to the first valid process node captured for the certain animation production area in the next unit monitoring cycle. When the efficiency value is less than or equal to the efficiency prediction value, feedback is sent to the management terminal that there is a process abnormality in a certain animation production area.

[0027] In order to better implement the above method, an animation image management method is also proposed. The system includes an animation production information sorting module, an effective process node identification management module, an efficiency value evaluation calculation module, a curve construction module, and an early warning management module;

[0028] The animation production information sorting module is used to sequentially capture and number the input operations entered by the authorized account with corresponding production authority in a plurality of animation production areas divided and set according to the production content of the target animation production on the animation production platform, and sequentially extract the animation effect images presented in the corresponding animation production area after entering each input operation;

[0029] The effective process node identification management module is used to establish an association tag between each input operation and the corresponding animation effect image; intercept the production process node in each animation production area; according to the presentation change of the animation effect image caused by the corresponding production process node in each animation production area, adjust the interception process of the production process node, and identify and extract the effective process node;

[0030] The efficiency value evaluation calculation module is used to calculate the corresponding efficiency of each valid process node according to the presentation change of the animation effect image caused by each interval input operation in each valid process node;

[0031] The curve construction module is used to set the unit monitoring cycle, perform curve fitting on the efficiency values ​​of all valid process nodes extracted from each animation production area in the current unit monitoring cycle, and obtain the efficiency value change curve corresponding to each animation production area in the current unit monitoring cycle;

[0032] The early warning management module is used to monitor the process changes of each animation production area within each unit monitoring cycle according to the efficiency value change curve, and provide early warning feedback to the management personnel based on the monitoring results.

[0033] Preferably, the effective process node identification management module includes a production process node interception unit and a production process node interception adjustment unit;

[0034] A production process node interception unit is used to establish an association tag between each input operation and the corresponding animation effect image; and to intercept the production process node in each animation production area;

[0035] The production process node interception adjustment unit is used to adjust the interception process of the production process nodes according to the presentation changes of the animation effect images caused by the corresponding production process nodes in each animation production area, and identify and extract the effective process nodes.

[0036] Preferably, the early warning management module includes a monitoring management unit and an early warning prompt unit;

[0037] A monitoring management unit, used to monitor the progress changes of each animation production area in each unit monitoring cycle according to the efficiency value change curve;

[0038] The early warning prompt unit is used to provide early warning prompts to management personnel based on the monitoring results.

[0039] Compared with the prior art, the beneficial effect achieved by the present invention is as follows: the present invention monitors the input operations of users with corresponding permissions in each animation production area of ​​the animation production platform, comprehensively compares the deviations of the animation effect images presented in the corresponding animation production areas after each input operation, and extracts the valid process nodes generated in each animation production area according to the results of the comprehensive comparison, and then evaluates the efficiency value of each valid process node and sorts out the changing trends of the efficiency value, thereby providing early warning prompts for the slow progress of the animation production work carried out in each animation production area, thereby achieving efficient supervision of the animation production platform. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0041] Figure 1 It is a flow chart of an animation image management method based on multi-source data of the present invention;

[0042] Figure 2 It is a structural schematic diagram of an animation image management system based on multi-source data of the present invention. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in 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.

[0044] See also Figure 1-Figure 2 The present invention provides a technical solution: an animation image management method based on multi-source data, the method comprising:

[0045] Step S1: in the animation production platform, in accordance with the production content of the target animation, input operations entered by the authorized account with corresponding production authority are captured and numbered in sequence, and the animation effect images presented in the corresponding animation production area after each input operation is entered are extracted in sequence;

[0046] Step S2: establishing an association tag between each input operation and the corresponding animation effect image; intercepting the production process node in each animation production area; adjusting the interception process of the production process node according to the presentation change of the animation effect image caused by the corresponding production process node in each animation production area, and identifying and extracting the valid process node;

[0047] Wherein, step S2 comprises:

[0048] Step S2-1: Assume that a production process node includes N input operations, where N ≥ 3. Whenever N input operations are captured sequentially in an arbitrary animation production area, a production process node corresponding to the arbitrary animation production area is constructed and generated; and according to the associated labels, corresponding animation effect images are extracted for each input operation constituting each production process node;

[0049] Step S2-2: in the generated production process node, the image similarity between the animation effect images corresponding to every two adjacent input operations is obtained in sequence; by default, the animation effect image corresponding to the first input operation in the generated production process node is used as the base reference image, and the image similarity between the animation effect image corresponding to each input operation starting from the second input operation and the base reference image is obtained in sequence;

[0050] Step S2-3: If P(S 1 ,S 2 )>P(S 1 ,S 3 )>...>P(S 1 ,S N ), the generated production process node is determined as a valid process node, where P(S 1 ,S 2 )、P(S 1 ,S 3 ), ..., P(S 1 ,S N ) respectively represent the image similarities between the animation effect images corresponding to the 2nd, 3rd, ..., Nth input operations in a certain production process node and the benchmark reference image;

[0051] Step S2-4: If the image similarity P(S 1 ,S k ) satisfies P(S 1 ,S k-1 ) <P(S 1 ,S k ), where 2≦k≦N, P(S 1 ,S k-1 ) represents the image similarity between the animation effect image corresponding to the k-1th input operation and the base reference image, removes the kth input operation from the generated production process node, triggers the input operation to be added in order, and generates a new production process node, until the new production process node is determined to be a valid process node;

[0052] For example, N = 6, if the image similarity P(S 1 ,S 4 ) satisfies P(S 1 ,S 3 ) <P(S 1 ,S 4), the fourth input operation is removed from the currently generated production process node, triggering the addition of one input operation in order to generate a new production process node. The added input operation is ranked sixth in the new production process node, and the input operation ranked fifth in the original production process node is ranked fourth in the new production node;

[0053] Step S3: Calculate the corresponding efficiency value for each valid process node according to the presentation change of the animation effect image caused by each interval input operation in each valid process node;

[0054] Wherein, step S3 comprises:

[0055] Step S3-1: extract each valid process node determined from each animation production area; obtain the total time T from capturing the first input operation to capturing the Nth input operation in each valid process node;

[0056] Step S3-2: Calculate the corresponding efficiency value β for each valid process node:

[0057] β=1 / [P(S 1 ,S 2 )+P(S 2 ,S 3 )]+...+P(S N-1 ,S N )] / (N-1)+1 / P(S 1 ,S N ) / T;

[0058] Among them, P(S 1 ,S 2 )、P(S 2 ,S 3 ), ..., P(S N-1 ,S N ) are respectively the image similarity between the animation effect image corresponding to the first input operation and the animation effect image corresponding to the second input operation, and the image similarity P(S) between the animation effect image corresponding to the second input operation and the animation effect image corresponding to the third input operation in each valid process node. 2 ,S 3 ), ..., the image similarity between the animation effect image corresponding to the Nth input operation and the animation effect image corresponding to the N-1th input operation; where P(S 1 ,S N ) represents the image similarity between the animation effect image corresponding to the 1st input operation and the animation effect image corresponding to the Nth input operation in each valid process node;

[0059] Step S4: setting a unit monitoring period, performing curve fitting on the efficiency values ​​of all valid process nodes extracted from each animation production area in the current unit monitoring period, and obtaining an efficiency value change curve corresponding to each animation production area in the current unit monitoring period;

[0060] Wherein, step S4 comprises: sequentially numbering all valid process nodes extracted from each animation production area in the current unit monitoring cycle, and extracting the efficiency value corresponding to each valid process node; for each animation production area, taking the sequence number corresponding to each valid process node extracted in the current unit monitoring cycle as x, and taking the efficiency value corresponding to each valid process node as y, performing curve fitting, and obtaining the efficiency value change curve y=Fx+b corresponding to each animation production area, wherein F represents the slope, and b is a constant;

[0061] Step S5: According to the efficiency value change curve, monitor the progress change of each animation production area in each unit monitoring cycle, and provide early warning prompts to the management personnel based on the monitoring results;

[0062] Wherein, step S5 comprises:

[0063] Step S5-1: If the slope of the efficiency value variation curve presented by a certain animation production area in the current unit monitoring period is F<0, and |F|>η, where η represents a threshold, a warning mark is made for the certain animation production area;

[0064] Step S5-2: Assume that the total number of valid process nodes captured for a certain animation production area in the current unit monitoring cycle is Q. When the first valid process node generated in the next unit monitoring cycle is extracted for a certain animation production area, input x=Q+1 into the efficiency value change curve constructed for the certain animation production area in the current unit monitoring cycle to obtain the efficiency prediction value. At the same time, obtain the efficiency value corresponding to the first valid process node captured for the certain animation production area in the next unit monitoring cycle. When the efficiency value is less than or equal to the efficiency prediction value, feedback is given to the management terminal that a process abnormality exists in a certain animation production area.

[0065] In order to better implement the above method, an animation image management method is also proposed. The system includes an animation production information sorting module, an effective process node identification management module, an efficiency value evaluation calculation module, a curve construction module, and an early warning management module;

[0066] The animation production information sorting module is used to sequentially capture and number the input operations entered by the authorized account with corresponding production authority in a plurality of animation production areas divided and set according to the production content of the target animation production on the animation production platform, and sequentially extract the animation effect images presented in the corresponding animation production area after entering each input operation;

[0067] The effective process node identification management module is used to establish an association tag between each input operation and the corresponding animation effect image; intercept the production process node in each animation production area; according to the presentation change of the animation effect image caused by the corresponding production process node in each animation production area, adjust the interception process of the production process node, and identify and extract the effective process node;

[0068] Among them, the effective process node identification management module includes a production process node interception unit and a production process node interception adjustment unit;

[0069] A production process node interception unit is used to establish an association tag between each input operation and the corresponding animation effect image; and to intercept the production process node in each animation production area;

[0070] A production process node interception adjustment unit is used to adjust the interception process of the production process node according to the presentation change of the animation effect image caused by the corresponding production process node in each animation production area, and identify and extract the effective process node;

[0071] The efficiency value evaluation calculation module is used to calculate the corresponding efficiency of each valid process node according to the presentation change of the animation effect image caused by each interval input operation in each valid process node;

[0072] The curve construction module is used to set the unit monitoring cycle, perform curve fitting on the efficiency values ​​of all valid process nodes extracted from each animation production area in the current unit monitoring cycle, and obtain the efficiency value change curve corresponding to each animation production area in the current unit monitoring cycle;

[0073] The early warning management module is used to monitor the process changes of each animation production area within each unit monitoring cycle according to the efficiency value change curve, and provide early warning prompts to the management personnel based on the monitoring results;

[0074] Among them, the early warning management module includes a monitoring management unit and an early warning prompt unit;

[0075] A monitoring management unit, used to monitor the progress changes of each animation production area in each unit monitoring cycle according to the efficiency value change curve;

[0076] The early warning prompt unit is used to provide early warning prompts to management personnel based on the monitoring results.

[0077] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0078] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An animation image management method based on multi-source data, characterized in that: The method comprises: Step S1: in the animation production platform, in accordance with the production content of the target animation, input operations entered by the authorized account with corresponding production authority are captured and numbered in sequence, and the animation effect images presented in the corresponding animation production area after each input operation is entered are extracted in sequence; Step S2: establishing an association tag between each input operation and the corresponding animation effect image; intercepting the production process node in each animation production area; adjusting the interception process of the production process node according to the presentation change of the animation effect image caused by the corresponding production process node in each animation production area, and identifying and extracting the valid process node; Step S3: calculating the corresponding efficiency value for each valid process node according to the presentation change of the animation effect image caused by each interval input operation in each valid process node; Step S4: setting a unit monitoring period, performing curve fitting on the efficiency values ​​of all valid process nodes extracted from each animation production area in the current unit monitoring period, and obtaining an efficiency value change curve corresponding to each animation production area in the current unit monitoring period; Step S5: monitoring the progress changes of each animation production area in each unit monitoring cycle according to the efficiency value change curve, and providing early warning feedback to the management personnel according to the monitoring results; The step S2 comprises: Step S2-1: Assume that a production process node includes N input operations, where N ≥ 3. Whenever N input operations are cumulatively captured sequentially in any animation production area, a production process node corresponding to the arbitrary animation production area is constructed and generated; and according to the associated tags, corresponding animation effect images are extracted for each input operation constituting each production process node; Step S2-2: in the generated production process node, the image similarity between the animation effect images corresponding to every two adjacent input operations is obtained in sequence; by default, the animation effect image corresponding to the first input operation in the generated production process node is used as the base reference image, and the image similarity between the animation effect image corresponding to each input operation starting from the second input operation and the base reference image is obtained in sequence; Step S2-3: If P(S 1 ,S 2 )>P(S 1 ,S 3 )>...>P(S 1 ,S N ), the generated production process node is determined as a valid process node, where P(S 1 ,S 2 )、P(S 1 ,S 3 ), ..., P(S 1 ,S N ) respectively represent the image similarities between the animation effect images corresponding to the second, third, ..., Nth input operations in the certain production process node and the benchmark reference image; Step S2-4: If the image similarity P(S 1 ,S k ) satisfies P(S 1 ,S k-1 ) <P(S 1 ,S k ), where 2≦k≦N, P(S 1 ,S k-1 ) represents the image similarity between the animation effect image corresponding to the k-1th input operation and the benchmark reference image, removes the kth input operation from the generated production process node, triggers the input operation to be added in sequence, and generates a new production process node, until the new production process node is determined to be a valid process node; The step S3 comprises: Step S3-1: extract each valid process node determined from each animation production area; obtain the total time T from capturing the first input operation to capturing the Nth input operation in each valid process node; Step S3-2: Calculate the corresponding efficiency value β for each valid process node: β=1 / [[P(S 1 ,S 2 )+P(S 2 ,S 3 )+...+P(S N-1 ,S N )] / (N-1)]+1 / [P(S 1 ,S N ) / T]; Among them, P(S 1 ,S 2 )、P(S 2 ,S 3 ), ..., P(S N-1 ,S N ) are respectively the image similarity between the animation effect image corresponding to the first input operation and the animation effect image corresponding to the second input operation, and the image similarity P(S) between the animation effect image corresponding to the second input operation and the animation effect image corresponding to the third input operation in each valid process node. 2 ,S 3 ), ..., the image similarity between the animation effect image corresponding to the Nth input operation and the animation effect image corresponding to the N-1th input operation; where P(S 1 ,S N ) represents the image similarity between the animation effect image corresponding to the 1st input operation and the animation effect image corresponding to the Nth input operation in each valid process node.

2. The method for managing animation images based on multi-source data according to claim 1, characterized in that: The step S4 comprises: sequentially numbering all valid process nodes extracted from each animation production area within the current unit monitoring cycle, and extracting the efficiency value corresponding to each valid process node; for each animation production area, taking the serial number corresponding to each valid process node extracted within the current unit monitoring cycle as x, and taking the efficiency value corresponding to each valid process node as y, performing curve fitting to obtain the efficiency value change curve y=Fx+b corresponding to each animation production area, wherein F represents the slope and b is a constant.

3. The method for managing animation images based on multi-source data according to claim 2, characterized in that: The step S5 comprises: Step S5-1: If the slope of the efficiency value variation curve presented by a certain animation production area in the current unit monitoring period is F<0, and |F|>η, where η represents a threshold, a warning mark is made for the certain animation production area; Step S5-2: Assume that the total number of valid process nodes captured for the animation production area within the current unit monitoring period is Q. When the first valid process node generated in the next unit monitoring period is extracted for the animation production area, input x=Q+1 into the efficiency value change curve constructed for the animation production area within the current unit monitoring period to obtain the efficiency prediction value. At the same time, obtain the efficiency value corresponding to the first valid process node captured for the animation production area in the next unit monitoring period. When the efficiency value is less than or equal to the efficiency prediction value, feedback is sent to the management terminal that there is a process abnormality in the animation production area.

4. An animation image management system, used to execute the animation image management method based on multi-source data as claimed in any one of claims 1 to 3, characterized in that: The system includes an animation production information combing module, an effective process node identification management module, an efficiency value evaluation calculation module, a curve construction module, and an early warning management module; The animation production information sorting module is used to sequentially capture and number the input operations entered by the authorized account with corresponding production authority in a plurality of animation production areas divided and set according to the production content of the target animation production on the animation production platform, and sequentially extract the animation effect images presented in the corresponding animation production area after entering each input operation; The effective process node identification management module is used to establish an association tag between each input operation and the corresponding animation effect image; intercept the production process node in each animation production area; according to the presentation change of the animation effect image caused by the corresponding production process node in each animation production area, adjust the interception process of the production process node, and identify and extract the effective process node; The efficiency value evaluation and calculation module is used to calculate the corresponding efficiency of each valid process node according to the presentation change of the animation effect image caused by each interval input operation in each valid process node; The curve construction module is used to set a unit monitoring period, and perform curve fitting on the efficiency values ​​of all valid process nodes extracted from each animation production area in the current unit monitoring period, to obtain an efficiency value change curve corresponding to each animation production area in the current unit monitoring period; The early warning management module is used to monitor the process changes of each animation production area within each unit monitoring cycle according to the efficiency value change curve, and provide early warning feedback to the management personnel according to the monitoring results.

5. An animation image management system according to claim 4, characterized in that: The effective process node identification management module includes a production process node interception unit and a production process node interception adjustment unit; The production process node interception unit is used to establish an association tag between each input operation and the corresponding animation effect image; and to intercept the production process node in each animation production area; The production process node interception adjustment unit is used to adjust the interception process of the production process nodes according to the presentation changes of the animation effect images caused by the corresponding production process nodes in each animation production area, and identify and extract the effective process nodes.

6. An animation image management system according to claim 4, characterized in that: The early warning management module includes a monitoring management unit and an early warning prompt unit; The monitoring management unit is used to monitor the progress change of each animation production area in each unit monitoring cycle according to the efficiency value change curve; The early warning prompt unit is used to provide early warning prompts to management personnel based on the monitoring results.

Images