Convolutional neural network-based animation special effect digital camera and special effect production method

Abstract

The application relates to a kind of cartoon special effect digital cameras based on convolutional neural network and special effect generation method, belong to photography technical field, including camera body, the PCB function board being arranged on camera body, the button group being connected with PCB function board, main controller being arranged on PCB function board and CMOS photosensitive chip and LCD screen all being connected with main controller, main control ware includes image input unit, convolutional neural network cartoon special effect generation unit, image output unit, image coding unit, image storage unit, image decoding unit and logic control unit, through the analysis and adjustment processing of image of CMOS photosensitive chip collection image and image input unit, convolutional neural network cartoon special effect generation unit is combined with real style data and cartoon style data and is trained through style migration model, based on training data parameter weight, obtain interesting cartoon special effect, realize the cartoon special effect function of photographing video, satisfy the interesting of children, increase the interesting and creativity of children using camera.

Description

Technical Field

[0001] This invention belongs to the field of photography technology, and relates to a digital camera for animation special effects based on convolutional neural networks and a method for producing special effects, particularly to a digital camera for children with animation special effects based on convolutional neural networks and a method for producing animation special effects. Background Technology

[0002] A camera, or simply camera, is a device that uses optical imaging principles to form an image and records it using film. Many image-recording devices possess characteristics of cameras, such as medical imaging equipment and astronomical observation equipment. A camera is an optical instrument used for photography. Light reflected from the subject passes through the lens and the shutter, which controls the exposure, and is focused to form a latent image on photosensitive material inside a darkroom. After developing, this image becomes a permanent photograph; this technique is called photography. Digital cameras, on the other hand, convert optical signals into electrical signals for processing and storage.

[0003] With the rise of children's photography, children's digital cameras are gaining popularity among consumers compared to adult digital cameras, which are often bulky and complex for children to operate. Children's digital cameras play an indispensable role in cultivating children's aesthetic abilities, such as framing and composition. However, current children's digital cameras on the market have limited functionality, offering only basic photo and video recording and color filter functions. They lack the utilization of AI technology and innovative product design, failing to meet children's needs for fun and creativity. Summary of the Invention

[0004] In view of this, in order to solve the problem that existing children's digital cameras have limited functions, only having simple photo and video recording and color filter functions, lacking the utilization of AI technology and product creativity, and thus failing to meet children's fun and creativity, the present invention provides a digital camera with animation effects based on convolutional neural networks and a method for producing special effects, which can realize animation effects functions for photo and video recording, thus satisfying children's fun.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A digital camera for animation effects based on convolutional neural networks includes a camera body, a PCB function board set on the camera body, a button group connected to the PCB function board, a main controller set on the PCB function board, and a CMOS photosensitive chip and an LCD screen all connected to the main controller.

[0007] The main controller includes an image input unit connected to a CMOS image sensor chip, receiving image signals captured by the CMOS image sensor chip and performing analog-to-digital conversion; a convolutional neural network animation effects generation unit connected to the image input unit and converting the images transmitted by the image input unit into animation effects; an image output unit connected to an LCD screen, receiving animation effects images transmitted by the convolutional neural network animation effects generation unit and displaying them on the LCD screen; an image encoding unit connected to the convolutional neural network animation effects generation unit, receiving animation effects images transmitted by the convolutional neural network animation effects generation unit and encoding and compressing them; an image storage unit connected to the image encoding unit and storing the data sent by the image encoding unit; an image decoding unit connected to the image storage unit, receiving image data transmitted by the image storage unit, decoding it, and transmitting the decoded image signals to the image output unit; and a logic control unit connected to the button group, the image input unit, the convolutional neural network animation effects generation unit, the image output unit, the image encoding unit, the image storage unit, and the image decoding unit. The logic control unit performs logic control and data flow control through the button group.

[0008] Furthermore, the camera itself integrates a Wi-Fi module. Benefit: Images can be transmitted to other terminal devices via the Wi-Fi module.

[0009] Furthermore, the main controller also includes a data communication unit connected to the WIFI module. Beneficial effect: By connecting the data communication unit to the WIFI module, the camera can perform wireless data transmission.

[0010] Furthermore, the button group is connected to the data communication unit. Beneficial effect: The logic control unit performs logic control and controls the data flow through the designated button group connected to the data communication unit.

[0011] Furthermore, the output of the image encoding unit is connected to the data communication unit. Beneficial effect: The image encoding unit transmits the encoded and compressed data to the data communication unit, which then transmits the encoded and compressed data to the smart terminal for user viewing.

[0012] Furthermore, the output of the image storage unit is connected to the data communication unit. Beneficial effect: The image storage unit transmits the encoded and compressed data to the data communication unit, which then transmits the encoded and compressed data to the smart terminal for user viewing.

[0013] Furthermore, the image storage unit has a built-in SD card function. Benefit: Provides local data storage options via SD card.

[0014] Furthermore, the convolutional neural network animation effects generation unit combines real style data and animation style data and is trained through a style transfer model. Based on the parameter weights of the training data, an animation style model is obtained.

[0015] Furthermore, anime style data includes style features, texture features, and perceptual features.

[0016] Furthermore, the digital camera for animation special effects and the method for producing special effects based on convolutional neural networks include the following steps:

[0017] S1: Start the camera: When the camera starts, it loads a convolutional neural network animation effects program;

[0018] S2: Image Acquisition and Processing: The CMOS image sensor acquires images, and after analog-to-digital conversion, the raw data is transmitted to the image input unit of the main controller;

[0019] S3: Image Sharpness Analysis and Adjustment: The image input unit analyzes the sharpness of the raw data and adjusts the acquisition parameters of the CMOS photosensitive chip in real time based on the analysis results. The processed raw image data is then passed to the convolutional neural network animation effects generation unit.

[0020] S4: Animation Effects Generation: The convolutional neural network animation effects generation unit analyzes the image content, selects appropriate animation effects, and converts the image into animation effects;

[0021] S5: Animation special effects image transmission: The convolutional neural network animation special effects generation unit transmits animation special effects images to the image output unit and the image encoding unit;

[0022] S6: Anime Special Effects Image Display: The image output unit sends images with anime special effects to the LCD screen for users to view;

[0023] S7: Encoding, Compression and Storage: The image encoding unit encodes and compresses the image with animation effects, and sends the compressed data to the image storage unit for storage;

[0024] S8: Image playback: When the user needs to play back the image, the image storage unit transmits the data to the image decoding unit, and the decoded image is displayed on the LCD screen through the image output unit for the user to view.

[0025] S9: Smart Terminal Interaction: When a user needs to play back or download images on a smart terminal, the data communication unit transmits data from the image storage unit to the smart terminal, and the user can view or download the encoded and compressed data via WIFI or other means.

[0026] The beneficial effects of this invention are as follows:

[0027] 1. The digital camera with animation effects based on convolutional neural networks disclosed in this invention acquires images through a CMOS image sensor chip and analyzes and adjusts the images through an image input unit. The convolutional neural network animation effects generation unit combines real style data and animation style data and is trained through a style transfer model. Based on the parameter weights of the training data, interesting animation effects are obtained, realizing the animation effects function of taking photos and videos, satisfying children's fun, and increasing children's fun and creativity in using the camera.

[0028] 2. The digital camera for animation special effects based on convolutional neural networks disclosed in this invention enables the camera to communicate with smart terminals via a WIFI module and a data communication unit, allowing users to view and share photos of animation special effects in real time. Users can also replay or share their work at any time.

[0029] 3. The digital camera for animation special effects based on convolutional neural networks disclosed in this invention uses an image storage unit and an image decoding unit. The decoded image is displayed on an LCD screen through an image output unit for users to view, thus meeting users' playback needs.

[0030] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination, or may be learned from practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description

[0031] To make the objectives, technical solutions, and advantages of the present invention clearer, the preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, wherein:

[0032] Figure 1 This document presents the workflow diagrams for each unit in this implementation.

[0033] Figure 2 This is a flowchart illustrating how the convolutional neural network animation effects generation unit in this implementation obtains the animation style. Detailed Implementation

[0034] The following embodiments illustrate the implementation of the present invention through specific examples. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Unless otherwise specified, the following embodiments and features in the embodiments can be combined with each other.

[0035] The accompanying drawings are for illustrative purposes only and are schematic diagrams, not actual pictures. They should not be construed as limiting the invention. To better illustrate the embodiments of the invention, some parts in the drawings may be omitted, enlarged, or reduced, and do not represent the actual product dimensions. It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0036] In the accompanying drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components. In the description of the present invention, it should be understood that if terms such as "upper," "lower," "left," "right," "front," and "rear" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, the terms used to describe positional relationships in the drawings are only for illustrative purposes and should not be construed as limiting the present invention. For those skilled in the art, the specific meaning of the above terms can be understood according to the specific circumstances.

[0037] like Figures 1-2 The digital camera for animation effects based on convolutional neural networks shown includes a camera body, a PCB function board set on the camera body, a button group connected to the PCB function board, a main controller set on the PCB function board, and a CMOS image sensor and an LCD screen all connected to the main controller. In addition to the above basic functions, the camera body also has a WIFI module function, which sends images to other terminal devices through the WIFI module.

[0038] The main controller includes an image input unit, a convolutional neural network animation effects generation unit, an image output unit, an image encoding unit, an image storage unit, an image decoding unit, and a logic control unit. The main controller also incorporates a data communication unit that connects to the WIFI module, enabling the camera to perform wireless data transmission.

[0039] The image input unit is connected to the CMOS image sensor, receiving the image signals captured by the CMOS image sensor and performing analog-to-digital conversion. The image input unit performs sharpness analysis on these image signals and adjusts the acquisition parameters of the CMOS image sensor in real time based on the analysis results. These processed image signals are then transmitted to the convolutional neural network animation effects generation unit.

[0040] Reference Figure 2The convolutional neural network (CNN) animation effects generation unit is connected to the image input unit and converts the image transmitted by the image input unit into animation effects. It is a generative adversarial network or image diffusion model composed of convolutional neural networks. It combines real style data and animation style data and is trained through a style transfer model to learn the style features, texture features, and perceptual features of animation style images. Based on the parameter weights of the training data, a model that can generate animation effects from images is obtained.

[0041] Style transfer model training does not require pairing real images with anime images; it truly performs semantic-level style transfer, resulting in better performance.

[0042] The image output unit is connected to the LCD screen, receives the animation effect images transmitted by the convolutional neural network animation effect generation unit, and displays the image content with animation effects on the LCD screen for users to view.

[0043] The image encoding unit, connected to the convolutional neural network animation effects generation unit, receives the animation effects images transmitted by the convolutional neural network animation effects generation unit and encodes and compresses them. The output of the image encoding unit is connected to the data communication unit. The image encoding unit transmits the encoded and compressed data to the data communication unit, which then transmits the encoded and compressed data to the smart terminal for user viewing.

[0044] The image storage unit, connected to the image encoding unit, stores the data sent by the image encoding unit. To facilitate image data storage, an SD card is integrated into the image storage unit, providing a convenient storage method. The output of the image storage unit is connected to the data communication unit. The image storage unit transmits the encoded and compressed data to the data communication unit, which then transmits the encoded and compressed data to the smart terminal for user viewing.

[0045] The image decoding unit is connected to the image storage unit. It receives the image data transmitted by the image storage unit, decodes it, and transmits the decoded image signal to the image output unit, so that the decoded animation special effects image can be displayed on the LCD screen for users to view.

[0046] The logic control unit is connected to the button group, image input unit, convolutional neural network animation effects generation unit, image output unit, image encoding unit, image storage unit, and image decoding unit. Simultaneously, the button group is connected to the data communication unit, and the logic control unit performs logic control and controls the data flow through the configured button group to the data communication unit.

[0047] A digital camera for animation special effects based on convolutional neural networks and a method for producing special effects include the following steps:

[0048] S1: Start the camera: When the camera starts, it loads a convolutional neural network animation effects program;

[0049] S2: Image Acquisition and Processing: The CMOS image sensor acquires images, and after analog-to-digital conversion, the raw data is transmitted to the image input unit of the main controller;

[0050] S3: Image Sharpness Analysis and Adjustment: The image input unit analyzes the sharpness of the raw data and adjusts the acquisition parameters of the CMOS photosensitive chip in real time based on the analysis results. The processed raw image data is then passed to the convolutional neural network animation effects generation unit.

[0051] S4: Animation Effects Generation: The convolutional neural network animation effects generation unit analyzes the image content, selects appropriate animation effects, and converts the image into animation effects;

[0052] S5: Animation special effects image transmission: The convolutional neural network animation special effects generation unit transmits animation special effects images to the image output unit and the image encoding unit;

[0053] S6: Anime Special Effects Image Display: The image output unit sends images with anime special effects to the LCD screen for users to view;

[0054] S7: Encoding, Compression and Storage: The image encoding unit encodes and compresses the image with animation effects, and sends the compressed data to the image storage unit for storage;

[0055] S8: Image playback: When the user needs to play back the image, the image storage unit transmits the data to the image decoding unit, and the decoded image is displayed on the LCD screen through the image output unit for the user to view.

[0056] S9: Smart Terminal Interaction: When a user needs to play back or download images on a smart terminal, the data communication unit transmits data from the image storage unit to the smart terminal, and the user can view or download the encoded and compressed data via WIFI or other means.

[0057] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A digital camera for animation special effects based on convolutional neural networks, characterized in that, include: Camera body; The PCB functional board is mounted on the camera body; The button assembly is connected to the PCB function board. The main controller is located on the PCB function board; Both the CMOS image sensor and the LCD screen are connected to the main controller; The main controller includes: An image input unit is connected to the CMOS photosensitive chip and receives the image signal captured by the CMOS photosensitive chip and performs analog-to-digital conversion. A convolutional neural network animation effects generation unit is connected to the image input unit and converts the image transmitted by the image input unit into animation effects. An image output unit is connected to the LCD screen and receives animation effect images transmitted by the convolutional neural network animation effect generation unit and displays them on the LCD screen. The image encoding unit is connected to the convolutional neural network animation effects generation unit and receives the animation effects image transmitted by the convolutional neural network animation effects generation unit and encodes and compresses it. An image storage unit is connected to the image encoding unit and stores the data sent by the image encoding unit; An image decoding unit is connected to the image storage unit and receives image data transmitted by the image storage unit, decodes it, and transmits the decoded image signal to the image output unit. The logic control unit is connected to the button group, the image input unit, the convolutional neural network animation effects generation unit, the image output unit, the image encoding unit, the image storage unit, and the image decoding unit. The logic control unit performs logic control and data flow control through a keypad.

2. The digital camera for animation special effects based on a convolutional neural network as described in claim 1, characterized in that, The camera body integrates a WIFI module.

3. The digital camera for animation special effects based on a convolutional neural network as described in claim 2, characterized in that, The main controller also includes a data communication unit connected to the WIFI module.

4. The digital camera for animation special effects based on a convolutional neural network as described in claim 3, characterized in that, The button group is connected to the data communication unit.

5. The digital camera for animation special effects based on a convolutional neural network as described in claim 3, characterized in that, The output of the image encoding unit is connected to the data communication unit.

6. The digital camera for animation special effects based on a convolutional neural network as described in claim 3, characterized in that, The output of the image storage unit is connected to the data communication unit.

7. The digital camera for animation special effects based on a convolutional neural network as described in claim 1, characterized in that, The image storage unit has a built-in SD card function.

8. The digital camera for animation special effects based on a convolutional neural network as described in claim 1, characterized in that, The convolutional neural network animation effects generation unit combines real style data and animation style data and is trained through a style transfer model. Based on the training data parameter weights, an animation style model is obtained.

9. The digital camera for animation special effects based on a convolutional neural network as described in claim 8, characterized in that, The anime style data includes style features, texture features, and perceptual features.

10. A digital camera for animation special effects based on convolutional neural networks and a method for producing special effects, characterized in that, Includes the following steps: S1: Start the camera: When the camera starts, it loads a convolutional neural network animation effects program; S2: Image acquisition and processing: The CMOS image sensor acquires images, and after analog-to-digital conversion, the raw data is transmitted to the image input unit of the main controller; S3: Image Sharpness Analysis and Adjustment: The image input unit analyzes the sharpness of the raw data and adjusts the acquisition parameters of the CMOS photosensitive chip in real time based on the analysis results. The processed raw image data is then passed to the convolutional neural network animation effects generation unit. S4: Animation Effects Generation: The convolutional neural network animation effects generation unit analyzes the image content, selects appropriate animation effects, and converts the image into animation effects; S5: Animation special effects image transmission: The convolutional neural network animation special effects generation unit transmits animation special effects images to the image output unit and the image encoding unit; S6: Anime Special Effects Image Display: The image output unit sends images with anime special effects to the LCD screen for users to view; S7: Encoding, Compression and Storage: The image encoding unit encodes and compresses the image with animation effects, and sends the compressed data to the image storage unit for storage; S8: Image playback: When the user needs to play back the image, the image storage unit transmits the data to the image decoding unit, and the decoded image is displayed on the LCD screen through the image output unit for the user to view. S9: Smart Terminal Interaction: When a user needs to play back or download images on a smart terminal, the data communication unit transmits data from the image storage unit to the smart terminal, and the user can view or download the encoded and compressed data via WIFI or other means.

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