Fishing live broadcast system and fishing live broadcast method

Abstract

The invention relates to the technical field of live broadcast, in particular to a fishing live broadcast system and method, and the system comprises a data processing unit, and a visual collection unit and a wireless communication unit which are connected with the data processing unit. The visual acquisition unit is used for acquiring visual data in a preset live broadcast area, and the visual data comprises float state information and / or fish image information; the data processing unit is used for carrying out recognition processing according to the visual data to obtain a recognition result, the recognition result comprises the motion state of a float and / or fish state information, and the fish state information comprises at least one of the type, the size and the weight; and the wireless communication unit is used for communicating with a live broadcast platform and sending the visual data and the identification result to the live broadcast platform for display. Through the fishing live broadcast system provided by the invention, the participation sense and experience sense of audiences on live broadcast are greatly enhanced.

Description

Technical Field

[0001] This application relates to the field of live broadcast technology, and particularly to a fishing live broadcast system and a fishing live broadcast method. Background Art

[0002] Fishing activities carried out at night (hereinafter referred to as night fishing) are a popular form of leisure and entertainment. Night fishing not only allows fishermen to avoid the heat and strong sunlight during the day, but also effectively improves the success rate of fishing and brings a richer fishing experience. At the same time, with the continuous development and popularization of live broadcast technology, night fishing activities have gradually evolved from personal hobbies into popular content in online live broadcasts, attracting many viewers to watch and interact online, greatly enhancing the fun and influence of night fishing activities.

[0003] Although the night vision fishing underwater camera component and the autofocus night fishing lamp in the traditional solution improve the convenience and success rate of night fishing to a certain extent, they have limitations in function, such as being unable to collect the scenes on the water surface and underwater simultaneously, and lacking a live broadcast function. These drawbacks limit the further development of night fishing activities and the improvement of user experience. How to improve the user's night fishing live broadcast experience has become an urgent problem to be solved. Summary of the Invention

[0004] This application provides a fishing live broadcast system and a fishing live broadcast method to improve the live broadcast experience of users during night fishing.

[0005] In a first aspect, this application provides a fishing live broadcast system, which includes: a data processing unit, and a visual acquisition unit and a wireless communication unit respectively connected to the data processing unit;

[0006] The visual acquisition unit is used to collect visual data within a preset live broadcast area, and the visual data includes fish float state information and / or fish image information;

[0007] The data processing unit is used to perform recognition processing on the visual data to obtain a recognition result, and the recognition result includes the motion state of the fish float and / or fish state information, and the fish state information includes at least one of species, size, and weight;

[0008] The wireless communication unit is used to communicate with the live broadcast platform and send the visual data and the recognition result to the live broadcast platform for display.

[0009] In some embodiments, the fishing live broadcast system further includes an illumination unit, the illumination unit is connected to the data processing unit, and the illumination unit is used to perform illumination within the preset live broadcast area according to the illumination angle set by the user to obtain an illumination area;

[0010] The visual acquisition unit includes a first visual acquisition unit, and the first visual acquisition unit is used to collect visual data within the illumination area.

[0011] In some embodiments, the visual acquisition unit further includes a second visual acquisition unit, which is configured to acquire visual data within a preset live broadcast area according to the perspective of the angler.

[0012] In some embodiments, the fishing live broadcast system further includes a remote control unit, which is connected to the wireless communication unit and the data processing unit. The remote control unit is configured to communicate with a remote control terminal through the wireless communication unit and control the fishing live broadcast system according to the instructions sent by the remote control terminal.

[0013] In some embodiments, the fishing live broadcast system further includes an audio acquisition unit, which is connected to the data processing unit. The audio acquisition unit is configured to acquire audio data within the preset live broadcast area.

[0014] In some embodiments, the fishing live broadcast system further includes an image display unit, which is connected to the data processing unit. The image display unit is configured to display visual data and recognition results.

[0015] In some embodiments, the fishing live broadcast system further includes a positioning unit, which is connected to the data processing unit. The positioning unit is configured to obtain the location information of the fishing live broadcast system.

[0016] In a second aspect, the present application provides a fishing live broadcast method, which is applied to the above-mentioned fishing live broadcast system. The method includes:

[0017] The visual acquisition unit acquires visual data within the preset live broadcast area, and the visual data includes fish float state information and / or fish image information;

[0018] The data processing unit performs recognition processing on the visual data to obtain a recognition result, and the recognition result includes the motion state of the fish float and / or fish state information. The fish state information includes at least one of species, size, and weight;

[0019] The wireless communication unit communicates with the live broadcast platform and sends the visual data and the recognition result to the live broadcast platform for display.

[0020] In some embodiments, the data processing unit performs recognition processing on the visual data to obtain a recognition result, including:

[0021] Processing N consecutive frames of images in the visual data according to the Yolo algorithm to obtain the position information of the fish float;

[0022] Calculating the average height and average width of the pixels occupied by the part of the fish float exposed above the water surface according to the position information of the fish float;

[0023] When the average height and average width exceed a first preset threshold, calculate the change frequency of the average height and average width;

[0024] When the change frequency of the average height and average width exceeds a second preset threshold, it is determined that the movement state of the float is that a fish has bitten the bait under the float, otherwise it is determined that the movement state of the float is that the fish has not bitten the bait under the float.

[0025] In some embodiments, the data processing unit performs recognition processing on the visual data to obtain a recognition result, including:

[0026] Use the Yolo algorithm to identify the type of the target fish and obtain the type information;

[0027] Use the Yolo algorithm to calculate the actual size of the target fish according to the planar size of the target fish in the visual data and obtain the size information;

[0028] Use the grayscale algorithm to calculate the area occupied by the target fish in the planar size according to the planar size of the target fish in the visual data;

[0029] Calculate the weight of the target fish according to the area occupied by the target fish in the planar size and the type information of the target fish to obtain the weight information.

[0030] In a third aspect, the present application provides a computer device, including a memory, a processor, and a computer program stored on the memory, and the processor executes the computer program to implement the steps of the method described in the above aspect.

[0031] In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the method described in the above aspect are implemented.

[0032] In a fifth aspect, the present application provides a computer program product, including a computer program / instructions, and when the computer program is executed by a processor, the steps of the method described in the above aspect are implemented.

[0033] A fishing live broadcast system and a fishing live broadcast method provided by this application collect visual data in a preset live broadcast area in real time through a visual acquisition unit, including fish float state information and fish image information, which can clearly capture the subtle changes of the fish float and the dynamics of the fish, ensuring the accuracy and real-time nature of the data; the data processing unit performs recognition processing on the visual data to obtain the motion state of the fish float and the state information of the fish (species, size, weight, etc.), and can quickly and accurately analyze the characteristics of the fish, helping fishermen understand the fishing situation in a timely manner and improving the fishing efficiency and success rate; the wireless communication unit transmits the visual data and the recognition results to the live broadcast platform in real time, and the audience can remotely watch the fishing activity through the live broadcast. By integrating functions such as visual acquisition, intelligent recognition, real-time transmission, and live broadcast display, a comprehensive fishing live broadcast experience is provided for fishermen and the audience. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The present application will be described in more detail below based on embodiments and with reference to the accompanying drawings:

[0035] Figure 1 is a schematic structural diagram of a fishing live broadcast system provided by an embodiment of the present application;

[0036] Figure 2 is a schematic flowchart of a fishing live broadcast method provided by an embodiment of the present application;

[0037] Figure 3 is a schematic structural diagram of another fishing live broadcast system provided by an embodiment of the present application;

[0038] Figure 4 is a schematic structural diagram of a computer device provided by an embodiment of the present application.

[0039] In the accompanying drawings, the same components are denoted by the same reference numerals, and the drawings are not drawn to actual scale. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0040] In order to enable those skilled in the art to better understand the technical solutions of the present application, and to fully understand how the present application uses technical means to solve technical problems and achieve the corresponding technical effects, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The embodiments of the present application and each feature in the embodiments can be combined with each other without conflict, and the formed technical solutions are all within the protection scope of the present application. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0041] It should be noted that in the description and claims of this application and the above-mentioned drawings, terms such as "first" and "second" are used to distinguish similar objects, and do not necessarily describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present application described here can be implemented in an order other than those illustrated or described here. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0042] It should be noted that the steps shown in the flowchart of the drawings can be executed in a computer system such as a set of computer-executable instructions. And although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0043] Example 1

[0044] Figure 1 It is a schematic structural diagram of a fishing live broadcast system provided by an embodiment of the present application.

[0045] As shown in Figure 1 the figure, the fishing live broadcast system includes: a data processing unit, and a visual acquisition unit and a wireless communication unit respectively connected to the data processing unit.

[0046] The visual acquisition unit is used to acquire visual data within a preset live broadcast area, and the visual data includes fish float state information and / or fish image information.

[0047] The visual acquisition unit is usually composed of image acquisition devices such as cameras, including ordinary cameras, camera arrays, infrared cameras, 3D cameras, thermal imaging cameras, etc., and can be specifically selected according to actual situations, and will not be limited here.

[0048] The visual acquisition unit can be installed in a suitable position to cover the preset live broadcast area. For example, in the fishing live broadcast scenario by the fishpond, the camera is installed above the fishing rod and shoots downward at a certain angle to ensure that the water area where the fish float is located and the underwater area within a certain range can be clearly captured.

[0049] As an example rather than a limitation, when the fish float makes actions such as floating up and sinking due to a fish biting the hook in the water, the visual acquisition unit can record these dynamic pictures in real time. At the same time, if the fish swims to the underwater area that can be photographed by the camera, image information such as the shape and swimming posture of the fish can also be acquired, and the captured picture data constitutes the visual data.

[0050] The data processing unit is used to perform recognition processing based on the visual data to obtain a recognition result. The recognition result includes the movement state of the fishing float and / or the status information of the fish, and the fish status information includes at least one of the species, size, and weight.

[0051] The data processing unit usually includes chips with computing capabilities, processors, and corresponding algorithm software, and is responsible for in-depth analysis and processing of the visual data transmitted by the visual acquisition unit.

[0052] As an example and not a limitation, for the collected visual data, the data processing unit uses an image recognition algorithm to determine whether the float is an effective movement caused by a fish biting the hook, or is simply an invalid shaking caused by water fluctuations, etc. based on the shape changes, movement trajectory and other characteristics of the float; for fish images, the species of fish is identified by comparing with a large number of pre-stored fish atlases, and then the approximate size and weight of the fish are estimated based on information such as the proportion of the fish in the image, the relative relationship of the body length and known reference objects.

[0053] The recognition result can be understood as the key conclusion reached by the data processing unit after intelligent analysis. For example, the recognition result shows that the fishing float is in a rapid downward motion and that there is a carp underwater, approximately 30 cm long and weighing about 0.7 kg. This specific information allows viewers to intuitively understand the dynamics of the fishing scene.

[0054] The wireless communication unit is used to communicate with the live broadcast platform and send the visual data and recognition results to the live broadcast platform for display.

[0055] The wireless communication unit includes but is not limited to a 4G / 5G module, a Wi-Fi module, a Bluetooth module, etc., which is used to send data to the live broadcast platform.

[0056] It will be understood that wireless communication methods may include but are not limited to 3G / 4G / 5G communication, WiFi communication, Bluetooth communication, WiMAX communication, Zigbee communication, UWB (ultra wideband) communication, and other wireless communication methods currently known or developed in the future.

[0057] As an example and not a limitation, when the data processing unit obtains the identification results that the fishing float is in a floating state after being bitten by a fish, the type of fish is crucian carp, and the weight is about 0.3 kg, the wireless communication unit will package and send these results and the original fishing float and fish images of the visual acquisition unit in accordance with the format requirements of network data transmission, and finally transmit them to the server side of the live broadcast platform via communication facilities such as base stations for subsequent display by the live broadcast platform.

[0058] Compared with the traditional fishing live broadcast method, viewers can only roughly understand the situation of fish biting the hook through the host's oral description or camera switching. The information obtained is not timely and accurate. Through the fishing live broadcast system in this application, viewers can see the precise movement state of the float in real time, and at the same time know information such as the type and size of the fish underwater, and can capture every key moment of fishing, greatly enhancing the viewers' sense of participation and experience in the live broadcast.

[0059] In addition, during the fishing process, anglers may make misjudgments due to factors such as light and angle when observing the float with the naked eye. For example, mistaking the water wave shaking for a fish biting the hook and frequently lifting the rod, resulting in many empty hook situations. The fishing live broadcast system in this application can help anglers accurately judge when to lift the rod based on the recognition result of the float movement state, reducing ineffective operations; and after understanding the fish state information, anglers can also adjust strategies such as bait and fishing methods according to the characteristics of the target fish species. For example, assuming the recognition result shows that there are mostly small crucian carps underwater, the angler can change to a smaller-sized bait that is more suitable for eating, thereby increasing the success rate of fishing and enhancing the angler's live broadcast experience.

[0060] Example 2

[0061] In some embodiments, the fishing live broadcast system further includes an illumination unit. The illumination unit is connected to the data processing unit. The illumination unit is used to perform illumination within a preset live broadcast area according to the illumination angle set by the user to obtain an illumination area. The visual acquisition unit includes a first visual acquisition unit, and the first visual acquisition unit is used to acquire visual data within the illumination area.

[0062] The illumination unit can include LED lights, incandescent lights, halogen lights, adjustable-angle spotlights, etc. The specific illumination light source can be selected according to the actual situation and is not limited here.

[0063] The first visual acquisition unit can either be a camera installed on the water or a camera installed underwater. The specific model of the camera is not limited here.

[0064] It can be understood that when fishing live in low light or at night, the illumination unit can provide sufficient light for the float and the surrounding water area, enabling the first visual acquisition unit to capture clear pictures. For example, when using an LED light as the illumination unit and an underwater camera as the first visual acquisition unit, after the LED light illuminates the float area, the underwater camera can more clearly capture the actions of the float such as floating up and sinking, avoiding blurred pictures or excessive noise caused by insufficient light, and allowing viewers to accurately understand the situation of fish biting the hook.

[0065] The cooperation between the illumination unit and the first visual acquisition unit provides better visual data for the data processing unit, helping to more accurately identify the float state and fish information, thereby enhancing the experience of the live broadcast.

[0066] In some embodiments, the visual acquisition unit further includes a second visual acquisition unit, which is configured to acquire visual data within a preset live broadcast area according to the perspective of the angler.

[0067] The perspective of the angler refers to the range and angle of the scene that the angler sees through his own eyes during the actual fishing process. It usually includes the float, the fishing rod, the water surface, and the surrounding environment, etc. This perspective is subjective and is closely related to the actual position, sitting posture, and observation direction of the angler, and can be adjusted according to the actual situation.

[0068] The second visual acquisition unit can be a wide-angle camera, a binocular camera, etc., and can be adjusted according to the actual perspective of the angler to ensure that the captured image is consistent with the scene seen by the angler.

[0069] The wide-angle camera can be installed near the angler to simulate the angler's field of view and capture a wider scene, including the float, the fishing rod, and the surrounding environment. The binocular camera can capture images with depth information by simulating human binocular vision, providing a more realistic visual experience for the angler.

[0070] By simulating the angler's perspective through the second visual acquisition unit, the audience can more realistically feel the actual perspective of fishing, increasing the fun and interactivity of the live broadcast.

[0071] In some embodiments, the fishing live broadcast system further includes a remote control unit, which is connected to the wireless communication unit and the data processing unit. The remote control unit is configured to communicate with a remote control terminal through the wireless communication unit and control the fishing live broadcast system according to the instructions sent by the remote control terminal.

[0072] By way of example and not limitation, the remote control unit includes a Remote Terminal Unit (RTU), a Telematics Control Unit (TCU), and a Remote Control Unit (RCU).

[0073] RTU is a device for remote data acquisition, control, and communication. It can receive instructions from a remote control terminal (such as a mobile phone, a computer, etc.) and control various components in the fishing live broadcast system through the wireless communication unit.

[0074] For example, the RTU can control the angle and focal length of a camera, adjust the brightness and angle of the lighting unit, or can also remotely start or stop a live broadcast. Through the RTU, users can send instructions via a mobile phone or computer from a location far away from the live broadcast site (such as at home, in the office, etc.), and adjust the live broadcast image and device status in real time, enhancing the flexibility and interactivity of the live broadcast.

[0075] The TCU is an embedded system, usually for remote monitoring and control, but can also play a similar role in a fishing live broadcast system.

[0076] For example, the TCU can receive instructions sent by a remote control terminal via a wireless network and control the operating status of the live broadcast device, such as adjusting the shooting angle of the camera, controlling the switch of the lighting unit, etc. Using the TCU allows users to remotely control the fishing live broadcast system via a mobile phone APP or a web page anywhere with network access, improving the convenience of the live broadcast and the user experience.

[0077] The RCU is a general-purpose remote control device. The RCU can receive instructions sent by a remote terminal via a wireless communication unit and control devices such as cameras and lighting units in the fishing live broadcast system.

[0078] Using the RCU allows users to control the live broadcast device through a simple operation interface (such as a mobile phone APP) from a location far away from the live broadcast site, improving the flexibility and operational convenience of the live broadcast.

[0079] Suppose a fishing live streamer is broadcasting outdoors. He can send instructions via the remote control APP on his mobile phone and control the angle of the camera installed near the fishing rod through the RTU or TCU, keeping it always aimed at the float and the water surface. At the same time, he can adjust the brightness of the lighting unit to ensure a clear image. In this way, even if the live streamer is not next to the camera, he can adjust the device at any time to optimize the live broadcast effect.

[0080] Using remote control units (such as RTU, TCU, or RCU) can make the fishing live broadcast system more intelligent and convenient. Users can send instructions via a remote terminal (such as a mobile phone or computer) to adjust the status of the live broadcast device in real time, improving the flexibility of the live broadcast.

[0081] In some embodiments, the fishing live broadcast system further includes an audio collection unit, which is connected to the data processing unit and is used to collect audio data in a preset live broadcast area.

[0082] The audio collection unit can include a microphone, an audio capture card, etc. The audio collection unit can be external or internal, and can be specifically set according to the actual situation.

[0083] For example, a microphone can be used as the audio acquisition unit. After the sound signal collected by the microphone is processed by the data processing unit, it is then sent to the live streaming platform through the wireless communication unit. In this way, when watching the live stream, the audience can not only see the fishing scene, but also hear the sound of the fish biting the hook, the sound of the water flow, and the commentary of the host, which can enable the audience to obtain a more comprehensive sensory experience.

[0084] In some embodiments, the fishing live streaming system further includes an image display unit, which is connected to the data processing unit and is used to display visual data and recognition results.

[0085] The image display unit can include an LCD display screen, an OLED display screen, a HUD projection display unit, or other display screens.

[0086] As an example but not limitation, an LCD display screen can be used as the image display unit. This display screen receives the images of the fishing float and fish collected by the visual acquisition unit through the data processing unit and displays the recognition results in real time. At the same time, the angler can also view the live stream on their own smart phone and adjust the angle of the camera and the lighting intensity. The audience can then watch the live stream on their mobile devices through the live streaming platform and see the clear dynamics of the fishing float and the images of the fish.

[0087] By using the display screens of LCD, OLED, HUD, or mobile devices, a higher-quality visual experience can be provided, enabling the audience to more clearly understand the situation at the fishing site.

[0088] In some embodiments, the fishing live streaming system further includes a positioning unit, which is connected to the data processing unit and is used to obtain the location information of the fishing live streaming system.

[0089] The positioning unit can include a Global Positioning System (GPS) module, a BeiDou Navigation Satellite System (BDS) module, a Wi-Fi positioning module, a Bluetooth positioning module, etc. The specific positioning unit can be selected according to the actual situation and is not limited here.

[0090] As an example but not limitation, a GPS module can be used as the positioning unit. When the live stream starts, the GPS module obtains the location information of the fishing spot in real time and sends this information to the live streaming platform through the data processing unit and the wireless communication unit. When watching the live stream, the audience can see the longitude and latitude information of the fishing location displayed below the live stream screen, or they can also view the environment around the fishing spot through the corresponding map service.

[0091] Adding a positioning unit to the fishing live streaming system can obtain and display the location information of the fishing live stream in real time, enhancing the interactivity and information richness of the live stream.

[0092] Example 3

[0093] Figure 2 It is a schematic flowchart of a fishing live broadcast method provided by an embodiment of the present application.

[0094] This embodiment provides a fishing live broadcast method, which is applied to the above-mentioned fishing live broadcast system. The method includes the following steps S201 to S203.

[0095] S201. The visual acquisition unit acquires visual data within a preset live broadcast area.

[0096] The visual data includes fish float state information and / or fish image information.

[0097] As an example rather than a limitation, a high-definition camera is used as the visual acquisition unit, which is installed near the fishing rod or at an appropriate position and is aimed at the fish float and the area under the water surface.

[0098] The visual data includes fish float state information (such as actions of the fish float rising and falling) and fish image information (such as the shape and swimming posture of the fish).

[0099] The visual acquisition unit can provide clear and real-time visual data, providing high-quality input for subsequent recognition processing and ensuring that the system can accurately capture the dynamics of the fish float and fish.

[0100] S202. The data processing unit performs recognition processing based on the visual data to obtain a recognition result.

[0101] The recognition result includes the motion state of the fish float and / or fish state information, and the fish state information includes at least one of species, size, and weight.

[0102] The data processing unit analyzes the acquired visual data through an image recognition algorithm. For example, it recognizes information such as the motion state of the fish float and the species, size, and weight of the fish.

[0103] For the recognition of the fish float state, it can be determined whether a fish has taken the bait by analyzing features such as the motion trajectory and shape change of the fish float. For the recognition of fish information, the fish image can be segmented and feature extracted, and then the size of the fish can be calculated.

[0104] Through the recognition by the data processing unit, the motion state of the fish float and the detailed information of the fish can be quickly and accurately recognized, providing richer data support for the live broadcast.

[0105] S203. The wireless communication unit communicates with the live broadcast platform and sends the visual data and the recognition result to the live broadcast platform for display.

[0106] The wireless communication unit communicates with the live broadcast platform via wireless communication technologies such as 4G, 5G, or Wi-Fi. The collected visual data and the recognition results obtained by the data processing unit are packaged and sent to the live broadcast platform, which then displays this information to the audience in real time.

[0107] It can be understood that the above-mentioned wireless communication methods may include but are not limited to 3G / 4G / 5G communication, WiFi communication, Bluetooth communication, WiMAX communication, Zigbee communication, UWB (ultra wideband) communication, and other wireless communication methods currently known or to be developed in the future.

[0108] By way of example and not limitation, data compression and transmission optimization technologies can be employed to ensure efficient data transmission within limited bandwidth. For example, the video bitrate can be dynamically adjusted based on network conditions. In a live fishing video, if network bandwidth is unstable, the video resolution or frame rate can be automatically reduced to ensure smooth streaming.

[0109] This method realizes the real-time transmission of live broadcast content. The audience can see the pictures of the fishing scene and the recognition results simultaneously, which enhances the interactivity and fun of the live broadcast.

[0110] In some embodiments, the data processing unit performs recognition processing based on the visual data to obtain a recognition result, including: processing N consecutive frames of images in the visual data according to the Yolo algorithm to obtain the position information of the fishing float; calculating the average height and average width of the pixels occupied by the part of the fishing float exposed above the water surface according to the position information of the fishing float; when the average height and the average width exceed a first preset threshold, calculating the change frequency of the average height and the average width; when the change frequency of the average height and the average width exceeds a second preset threshold, determining that the movement state of the fishing float is that a fish has bitten the bait under the fishing float, otherwise it is determined that the movement state of the fishing float is that the fish has not bitten the bait under the fishing float.

[0111] The Yolo algorithm is a real-time target detection algorithm based on deep learning, suitable for the rapid identification and location of objects in dynamic scenes. In live fishing streaming systems, the Yolo algorithm can quickly and accurately detect and locate target objects such as fishing floats in visual data, and can promptly capture the position changes of fishing floats even in complex water environments.

[0112] The position of the fishing float refers to its specific coordinates within the image. This precise positional data is obtained by processing consecutive frames of image data using the Yolo algorithm. This positional information is the basis for calculating relevant parameters and determining its motion state, helping the system understand the real-time dynamics of the float on the water.

[0113] The average height and average width refer to the average values obtained by calculating the height and width of the pixels occupied by the part of the fishing float above the water surface. These two parameters can reflect the morphological characteristics of the fishing float on the water surface. When a fish bites the bait, the movement of the fishing float will cause changes in the morphology of the part above the water surface, thereby causing changes in the average height and average width.

[0114] The change frequency refers to the frequency at which the average height and average width of the fishing float change in consecutive frame images. By calculating the change frequency, the dynamic characteristics of the morphological changes of the fishing float can be understood, so as to judge whether it is a valid fish-biting bait signal and avoid misjudgment caused by other interference factors such as water surface fluctuations.

[0115] As an example rather than a limitation, the visual acquisition unit continuously acquires images in the fishing live broadcast area at a certain frame rate to ensure that the real-time dynamics of the fishing float can be captured. The data processing unit uses the Yolo algorithm to process the continuously acquired N-frame images and accurately detect the position information of the fishing float in each frame of the image. The Yolo algorithm can quickly identify the fishing float in the image and return its position coordinates in the image coordinate system, such as the upper left and lower right coordinates of the bounding box, etc. According to the obtained position information of the fishing float, calculate the average height and average width of the pixels occupied by the part of the fishing float above the water surface. By measuring the size of the fishing float in consecutive N-frame images and calculating the average value, relatively stable morphological parameters of the fishing float are obtained, so as to characterize the average morphological characteristics of the fishing float in the current state. First, compare the calculated average height and average width with the first preset threshold. If it exceeds this threshold, further calculate the change frequency of the average height and average width and compare it with the second preset threshold. If the change frequency also exceeds the second preset threshold, it is determined that the movement state of the fishing float is that a fish has bitten the bait under the fishing float; otherwise, it is considered that the fish has not bitten the bait.

[0116] By combining the Yolo algorithm to process and analyze consecutive frame images, the position and morphological changes of the fishing float can be accurately detected, effectively avoiding misjudgment caused by insufficient information or interference in a single frame of image, and improving the accuracy of identifying fish-biting bait signals. Through judgment by the first preset threshold and the second preset threshold, first screen the average height and average width of the fishing float. Only when it exceeds a certain range and the change frequency also meets the requirements, it is determined as a valid bait-biting signal. This multiple judgment method can effectively filter out the morphological changes of the fishing float caused by other non-bait factors such as water surface fluctuations and light changes, reduce the false alarm rate, and improve the reliability of the system.

[0117] In some embodiments, the data processing unit performs recognition processing based on visual data to obtain recognition results, including: using the Yolo algorithm to identify the species of the target fish to obtain species information; using the Yolo algorithm to calculate the actual size of the target fish according to the planar size of the target fish in the visual data to obtain size information; using a grayscale algorithm to calculate the area occupied by the target fish in the planar size according to the planar size of the target fish in the visual data; calculating the weight of the target fish according to the area occupied by the target fish in the planar size and the species information of the target fish to obtain weight information.

[0118] The species information refers to the species of the target fish identified by the Yolo algorithm, such as crucian carp, carp, grass carp, etc.

[0119] The planar size refers to the two-dimensional size of the target fish in the visual data (image or video frame), that is, the length and width, usually in pixels.

[0120] The actual size refers to the true length and width of the target fish calculated according to the planar size of the target fish and the parameters of the camera (such as focal length, shooting distance, etc.), usually in centimeters or meters.

[0121] As an example rather than a limitation, according to the bounding box of the target fish detected by the Yolo algorithm, obtain its planar size (length and width) in the image. Combining parameters such as the focal length and shooting distance of the camera, convert the planar size into the actual size through the principle of geometric optics.

[0122] As an example rather than a limitation, calculate the area occupied by the target fish in the grayscale image through image processing algorithms (such as threshold segmentation, contour detection, etc.). According to the species and area occupied by the target fish, query the pre-established corresponding relationship model between fish weight and area. Calculate the estimated weight of the target fish through methods such as interpolation or regression analysis.

[0123] The Yolo algorithm can quickly and accurately identify fish species, reducing the error of manual identification. Converting the planar size into the actual size through the principle of geometric optics improves the accuracy of size measurement. During the live broadcast, the species, size, and weight information of the fish are displayed in real time, allowing the audience to more intuitively understand the detailed information of the caught fish and enhancing the viewing experience.

[0124] In one implementation, an audio signal is collected through an audio acquisition unit (such as a microphone), and the acoustic fingerprint features of the fishline friction sound or fish biting the hook are extracted from the audio signal. In the standby state, the microphone continuously monitors the audio stream but remains in a low-power state. Only when specific acoustic fingerprint features are detected, the above-mentioned YOLO algorithm is awakened to perform real-time processing and recognition on the collected video data. Through the low-power monitoring and dynamic wake-up mechanism, system energy consumption can be reduced and battery life can be extended.

[0125] In one implementation, information on protected fish species corresponding to fishing locations, including the minimum catchable size, etc., is collected, sorted, and stored in a local database. Among them, the information on each protected fish species includes the species name, minimum catchable size, etc. Then, a legal database is deployed in the data processing unit of the fishing live broadcast system (or other storage units connected to the data processing unit). A camera is used to collect a real-time video stream, and fish are identified through the YOLO algorithm described above. For each identified fish, after obtaining its species and size information, the identification result is compared with the legal database to check whether it is a protected fish species or has an insufficient size. If a protected fish species or insufficient size is detected, the user is prompted to release it through the user interface, voice, or light flashing. Through real-time detection and prompting, fishing for protected fish species or fish with insufficient size is avoided, reducing the accidental catch of protected fish and improving the user's fishing experience.

[0126] Example 4

[0127] Based on the above embodiments, this embodiment provides an application example.

[0128] Figure 3 It is a schematic structural diagram of another fishing live broadcast system provided by an embodiment of the present application.

[0129] As Figure 3 shown, a remotely controllable intelligent system for night fishing live broadcast includes a hardware system and a software system; the hardware system consists of a system body and a bracket; the system body includes a lighting unit, a visual acquisition unit 1, a visual acquisition unit 2, an audio acquisition unit, a wireless communication unit, an image display unit, a data processing unit, a positioning unit, and a power supply unit; the lighting unit is connected to the data processing unit and the power supply unit; the visual acquisition unit 1 and the visual acquisition unit 2 are respectively connected to the data processing unit and the power supply unit; the audio acquisition unit is connected to the data processing unit; the wireless communication unit is connected to the data processing unit; the positioning unit is connected to the data processing unit; the image display unit is connected to the data processing unit; the data processing unit is connected to the power supply unit.

[0130] The lighting unit is composed of a spotlight module with the function of emitting strong light and is responsible for illuminating the water surface fishing process during night fishing.

[0131] Both the visual acquisition unit 1 and the visual acquisition unit 2 are respectively composed of cameras. The visual acquisition unit 1 is located outside the system body and is connected through a flexible structure, and can be adjusted horizontally and vertically according to the requirements of the image acquisition angle to collect images of the area illuminated by the lighting unit. The visual acquisition unit 2 is located outside the system body and is connected through a flexible structure, and is adjusted horizontally and vertically according to the requirements of the image acquisition angle to collect video images of the main perspective of the angler.

[0132] The audio acquisition unit is composed of a sound collector. The wireless communication unit is composed of a wireless communication module. The image display unit is composed of a small liquid crystal display screen. The data processing unit is composed of a high-performance processor and peripheral circuits. The positioning unit is composed of a satellite navigation and positioning module. The power supply unit is equipped with a peripheral power circuit. The bracket is flexibly connected to the system body, responsible for the stability of the system body and can adjust the height.

[0133] The software system runs automatically after the system is powered on and has functions such as lighting control, visual acquisition, remote control, live broadcast, intelligent recognition, positioning acquisition, and audio acquisition, and can perform system upgrades.

[0134] The lighting control function realizes the opening, closing, lighting intensity adjustment, and lighting color selection by controlling the data processing unit.

[0135] The visual acquisition function is that after the software system starts running, it automatically loads the driver programs of the visual acquisition unit 1 and the visual acquisition unit 2, and reads the data of the two visual acquisition units.

[0136] The remote control function is to establish a point-to-point transmission path for wireless data transmission by the software system loading the driver program of the wireless communication unit.

[0137] The live broadcast function is that after the software system is started, it integrates the startup function of the live broadcast platform, and then connects the data read from the visual acquisition unit 1 and the visual acquisition unit 2 to the live broadcast platform.

[0138] The intelligent recognition function is completed by the intelligent water surface detection algorithm and the fish feature recognition algorithm; the intelligent water surface detection algorithm is used to detect the movement state of the fish float on the water surface, and the detection result can be displayed on the image display unit.

[0139] The intelligent water surface detection algorithm uses the Yolo algorithm to process the images of N consecutive frames in the video acquisition unit, detects the fish float on the water surface, calculates the average height and average width of the pixels occupied by the part of the fish float exposed above the water surface in the N frames of images. When the average height and average width of the pixels occupied by the part of the fish float exposed above the water surface in the N frames of images exceed the threshold H1, start to calculate the change frequency of the average height and average width of the pixels respectively. When the change frequency of the average height and average width exceeds the threshold H2, it is determined that there is a fish biting the bait under the fish float underwater, otherwise it is considered that the bait under the fish float has not been bitten.

[0140] The fish feature recognition algorithm is used to determine the type of fish, estimate the size of the fish, and estimate the weight of the fish. The recognition results can be displayed on the image display unit. The fish feature recognition algorithm uses the Yolo algorithm to identify the type of fish in the video; the fish feature recognition algorithm defines the distance between the fish and the video acquisition unit as the distance between the image coordinate system and the object coordinate system, and then uses the Yolo algorithm to mark the rectangular border of the plane size occupied by the identified fish, and then estimates the size of the fish according to the length relationship between the pixel point size in the image coordinate system and the object coordinate system; using the grayscale algorithm, estimate the area of the rectangle border occupied by the fish, and estimate the weight of the fish according to the determined fish type and the average weight of this type of fish.

[0141] The positioning function is that the software system loads the driver of the positioning unit, reads the data output by the reader positioning unit, and parses the data into position information.

[0142] The audio acquisition function is that the software system loads the driver of the audio acquisition unit and uses the audio acquisition unit to obtain external sound information.

[0143] After the remotely controllable intelligent system for night fishing live broadcast is turned on, the data processing unit automatically runs the system, loads the system initialization software, and performs initialization settings on the lighting unit, visual acquisition unit 1, visual acquisition unit 2, sound acquisition unit, wireless communication unit, image display unit, data processing unit, positioning unit, and power supply unit, and then runs the intelligent water surface detection algorithm and the fish feature recognition algorithm.

[0144] The system body is connected to the bracket through a flexible structure and placed on the night fishing platform. After the system is turned on, the lighting unit starts to work, and the angle of the system body is adjusted through the flexible structure to achieve lighting of the night fishing water area. Among them, the bracket is responsible for the stability of the system body and can adjust the height. The bracket can adopt a three-legged bracket and a four-legged bracket.

[0145] After the remotely controllable intelligent system for night fishing live broadcast is turned on, the positioning unit automatically obtains position information, and the specific position information is displayed on the image display unit and the mobile phone APP.

[0146] The visual acquisition unit 1 adjusts the visual acquisition unit 1 to align with the area irradiated by the lighting unit through a flexible structure and performs image acquisition. The acquired data is processed by the data unit and displayed on the image display unit, and at the same time, it is displayed on the mobile phone side through the wireless communication unit.

[0147] The visual acquisition unit 2 adjusts the visual acquisition unit 2 to align with the main perspective of the angler through a flexible structure and performs main perspective image acquisition. The acquired data is processed by the data unit and displayed on the image display unit, and at the same time, it is displayed on the mobile phone side through the wireless communication unit.

[0148] The audio acquisition unit is rigidly connected to the system body to collect the voice information of the angler in real time.

[0149] The remotely controllable intelligent system for night fishing live broadcast can be connected to a mobile phone through a wireless communication unit, and through the control software of the night fishing light system for remote control and live broadcast, it can realize the selection of the lighting color of the lighting unit, the adjustment and display of the lighting intensity, the image display of the visual acquisition unit 1, the image display of the visual acquisition unit 2, the control of the audio acquisition unit, the display of the position information, the display of the power supply power, and the display of the results of the intelligent water surface detection algorithm and the fish feature recognition algorithm.

[0150] When the fish feature recognition algorithm receives the key information of the angler, it will give the results corresponding to the keywords, and the results given are the type of fish, the size of the fish, and the weight of the fish.

[0151] The remotely controllable intelligent system for night fishing live broadcast is connected to a mobile phone through a wireless communication unit, and can be accessed to the live broadcast platform opened by the mobile phone through the mobile phone APP matched with the system to display the acquisition pictures of the visual acquisition unit 1 and the visual acquisition unit 2 in real time.

[0152] The power supply unit can be charged by a wired method, and the battery pack of the power supply unit can be replaced and expanded.

[0153] The mobile phone APP of the night fishing light system for remote control and live broadcast can realize the selection of the lighting color of the lighting unit, the adjustment and display of the lighting intensity, the image display of the visual acquisition unit 1, the image display of the visual acquisition unit 2, the control of the audio acquisition unit, the display of the position information, the display of the power supply power, and the display of the results of the intelligent water surface detection algorithm and the fish feature recognition algorithm, and can realize system upgrade through wired connection and wireless connection methods.

[0154] The technical solution of this application has the following advantages:

[0155] 1) By realizing lighting, visual acquisition, and sound acquisition through an all-in-one machine, the night fishing lighting and live broadcast can be carried out simultaneously, which can meet the personalized needs of live broadcast enthusiasts;

[0156] 2) Through the mobile phone APP, the control of the light, the control of video acquisition, and the recognition of fish features can be realized;

[0157] 3) Through the integration of the hardware system and the realization of software functions, the experience and fun of the angler's night fishing live broadcast are improved.

[0158] Example 5

[0159] Based on the above embodiments, the present embodiment provides a computer device, including a memory, a processor, and a computer program stored on the memory, and the processor executes the computer program to implement the steps of the method described in the above embodiments.

[0160] In some embodiments of the present embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and characterized in that when the computer program is executed by a processor, the steps of the method described in the above embodiments are implemented.

[0161] In some embodiments of the present embodiment, a computer program product is provided, including a computer program / instructions, and characterized in that when the computer program is executed by a processor, the steps of the method described in the above embodiments are implemented.

[0162] The processor may include, but is not limited to, for example, one or more processors or microprocessors, etc. Each processor may be implemented by an application specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field programmable gate array (FPGA), a controller, a microcontroller, a microprocessor, or other electronic components, and is used to execute the method in the above embodiments.

[0163] The computer-readable storage medium may be implemented by any type of volatile or non-volatile storage device or a combination thereof. The computer-readable storage medium may include, but is not limited to, for example, a random access memory (RAM), a read-only memory (ROM), a flash memory, an EPROM memory, an EEPROM memory, a register, a computer storage medium (such as a hard disk, a floppy disk, a solid state drive, a removable disk, a CD-ROM, a DVD-ROM, a Blu-ray disc, etc.).

[0164] The computer-readable storage medium may also store at least one computer-executable program / instructions, such as computer-readable instructions. The computer-readable storage medium includes, but is not limited to, for example, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory, etc. The computer-readable storage medium may include, for example, read-only memory (ROM), hard disk, flash memory, etc. For example, the non-transitory computer-readable storage medium may be connected to a computing device such as a computer. Then, when the computing device runs the computer-readable instructions stored on the computer-readable storage medium, the various methods described above may be performed.

[0165] In addition, the computer device may further include (but is not limited to) a data bus, an input / output (I / O) bus, a display, and input / output devices (such as a keyboard, a mouse, a speaker, etc.).

[0166] The processor may communicate with external devices via the I / O bus through a wired or wireless network.

[0167] In one embodiment, the at least one computer-executable instruction may also be compiled into or form a software product / computer program product, and when one or more computer-executable instructions are run by the processor, the various functions and / or method steps in the embodiments described in this technology are executed.

[0168] In the embodiments provided in this application, it should be understood that the disclosed devices and methods may also be implemented in other ways. The device embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architectures, functions, and operations of the devices, methods, and computer program products according to multiple embodiments of this application. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code, and the above-mentioned module, program segment, or part of code includes one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order from that marked in the accompanying drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and the combination of blocks in the block diagram and / or flowchart, may be implemented by a dedicated hardware-based system for performing the specified functions or actions, or may be implemented by a combination of dedicated hardware and computer instructions.

[0169] It should be noted that in this application, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, such that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element limited by the statement "comprising an..." does not exclude the existence of additional identical elements in the process, method, article or device comprising the element.

[0170] Although the embodiments disclosed in this application are as above, the above content is only an embodiment adopted for the convenience of understanding this application and is not intended to limit this application. Any person skilled in the art within the technical field to which this application pertains may make any modifications and changes in the form of implementation and details without departing from the spirit and scope disclosed in this application. However, the scope of patent protection of this application shall still be subject to the scope defined by the appended claims.

Claims

1. A fishing live broadcast system, characterized in that, The fishing live broadcast system includes: a data processing unit, a visual acquisition unit, and a wireless communication unit that are respectively connected to the data processing unit; The visual acquisition unit is used to acquire visual data within a preset live broadcast area, and the visual data includes fish float state information and / or fish image information; The data processing unit is used to perform recognition processing based on the visual data to obtain a recognition result, and the recognition result includes the movement state of the fish float and / or fish state information, and the fish state information includes at least one of species, size, and weight; The wireless communication unit is used to communicate with the live broadcast platform and send the visual data and the recognition result to the live broadcast platform for display.

2. The fishing live broadcast system according to claim 1, wherein The fishing live broadcast system further includes an illumination unit, the illumination unit is connected to the data processing unit, and the illumination unit is used to perform illumination within the preset live broadcast area according to the illumination angle set by the user to obtain an illuminated area; The visual acquisition unit includes a first visual acquisition unit, and the first visual acquisition unit is used to acquire visual data within the illuminated area.

3. The fishing live broadcast system according to claim 2, wherein The visual acquisition unit further includes a second visual acquisition unit, and the second visual acquisition unit is used to acquire the visual data within the preset live broadcast area from the perspective of the angler.

4. The fishing live broadcast system according to any one of claims 1-3, characterized in that, The fishing live broadcast system further includes a remote control unit, the remote control unit is connected to the wireless communication unit and the data processing unit, and the remote control unit is used to communicate with a remote control terminal through the wireless communication unit and control the fishing live broadcast system according to the instructions sent by the remote control terminal.

5. The fishing live broadcast system according to any one of claims 1-3, characterized in that, The fishing live broadcast system further includes an audio acquisition unit, the audio acquisition unit is connected to the data processing unit, and the audio acquisition unit is used to acquire audio data within the preset live broadcast area.

6. The fishing live broadcast system according to any one of claims 1-3, characterized in that, The fishing live broadcast system further includes an image display unit, the image display unit is connected to the data processing unit, and the image display unit is used to display the visual data and the recognition result.

7. The fishing live broadcast system according to any one of claims 1-3, characterized in that, The fishing live broadcast system further includes a positioning unit, the positioning unit is connected to the data processing unit, and the positioning unit is used to obtain the position information of the fishing live broadcast system.

8. A fishing live broadcast method, characterized in that, Applied to the fishing live broadcast system according to any one of claims 1-7, the method includes: The visual acquisition unit acquires visual data within a preset live broadcast area, and the visual data includes fish float state information and / or fish image information; The data processing unit performs recognition processing based on the visual data to obtain a recognition result, and the recognition result includes the movement state of the fish float and / or fish state information, and the fish state information includes at least one of species, size, and weight; The wireless communication unit communicates with the live broadcast platform and sends the visual data and the recognition result to the live broadcast platform for display.

9. The fishing live broadcast method according to claim 8, characterized in that, The data processing unit performs recognition processing based on the visual data to obtain a recognition result, including: Processing continuous N-frame images in the visual data according to the Yolo algorithm to obtain the position information of the fish float; Calculate the average height and average width of the pixels occupied by the part of the float exposed above the water surface according to the position information of the float; When the average height and average width exceed the first preset threshold, calculate the change frequency of the average height and average width; When the change frequency of the average height and average width exceeds the second preset threshold, it is determined that the movement state of the float is that a fish has bitten the bait under the float, otherwise it is determined that the movement state of the float is that the fish has not bitten the bait under the float.

10. The fishing live broadcast method according to claim 8, wherein, The data processing unit performs recognition processing on the visual data to obtain a recognition result, including: Use the Yolo algorithm to identify the species of the target fish to obtain species information; Use the Yolo algorithm to calculate the actual size of the target fish according to the planar size of the target fish in the visual data to obtain size information; Use the grayscale algorithm to calculate the area occupied by the target fish in the planar size according to the planar size of the target fish in the visual data; Calculate the weight of the target fish according to the area occupied by the target fish in the planar size and the species information of the target fish to obtain weight information.

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