CN108509931B - Football wonderful video capturing method and system - Google Patents
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Abstract
The invention provides a football wonderful video capturing method, which comprises the following steps: capturing a first brightness change of a football video; when the first brightness change is larger than a preset first threshold value, one or more video frames after the first brightness change are extracted; performing image processing on the video frame to obtain a video frame after the image processing; obtaining feature information in one or more video frames based on the video frames after the image processing; presetting a plurality of video frame judgment threshold values; determining a category of the highlight event; recording the video after the first brightness change, and capturing a second brightness change in the video after the first brightness change is recorded; and stopping recording the video when the second brightness change is larger than a preset second threshold value. The football wonderful video method can reduce the computer operation amount, has strong video pertinence, highlights the special charm of the sports work of the football, and is beneficial to the popularization of the sports of the football.
Description
Technical Field
The invention relates to the field of intelligent sports devices, in particular to a football wonderful video capturing method and a football wonderful video capturing system.
Background
Sports is a complex social culture phenomenon, which takes physical and intellectual activities as basic means, and achieves conscious, purposeful and organized social activities of promoting overall development, improving physical quality and overall education level, enhancing physical fitness and sports ability, improving life style and improving life quality according to laws such as human growth and development, skill formation, function improvement and the like. With the expansion of international interaction, the scale and level of sports business development is an important mark for measuring the development progress of a country and a society, and becomes an important means for foreign exchange and cultural communication of the country. At present, football has become a popular global sport, has the reputation of "world first sport", and is the most influential single sport in the world's sports world.
In the past, sports games are traditionally watched through television broadcasting, however, with the rapid development of multimedia technology and internet, the demand of multimedia information is increasing, multimedia data integrating image, audio and text information is increasing in a geometric explosion manner, and the traditional information processing method and technology cannot deal with the continuously increasing mass video data. Multimedia video is taken as a main media type, the influence on the aspects of education, life, entertainment and the like of people is more and more prominent, and video applications with novel functions, such as digital televisions, video on demand, video conferences, remote education and the like, are integrated into daily life at present. Due to the fact that factors such as unstructured data formats, large data size, rich and various representation contents and the like exist, how to effectively organize and manage mass data and how to mine valuable or interesting information of users from the mass video data so as to meet personalized requirements of the users can be a difficult problem for researchers in the field of video analysis and retrieval at present.
Sports videos are popular with viewers, have great commercial value, and are widely concerned by social circles and researchers. Sports video analysis and retrieval are used as an important branch of the video retrieval field, and mainly aim at various sports game videos, analyze low-level features of the videos, realize detection of specific semantic events and create video summaries. The sports video has the following characteristics: (1) the video is various, and relates to various game types such as basketball, football, table tennis, baseball, tennis, diving and the like; (2) the video content is rich and various, and comprises the contents of competition progress conditions, athlete information, a program guide room, advertisements and the like; (3) the video has long duration and huge data volume; (4) sports video types are different, professional terms and rules are different, and specific structure and rule definitions are needed for different video types.
The information disclosed in this background section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art.
Disclosure of Invention
The invention aims to provide a football highlight video capturing method and a football highlight video capturing system, so that the defects of the prior art are overcome.
The invention provides a football wonderful video capturing method, which comprises the following steps: capturing a first brightness change of a football video; when the first brightness change is larger than a preset first threshold value, one or more video frames after the first brightness change are extracted; performing image processing on the video frame to obtain a video frame after the image processing; obtaining feature information in one or more video frames based on the video frames after the image processing; presetting a plurality of video frame judgment threshold values; determining the category of the wonderful event based on the comparison relationship between the characteristic information and the plurality of video frame judgment threshold values; recording the video after the first brightness change, and capturing a second brightness change in the video after the first brightness change is recorded; and stopping recording the video when the second brightness change is larger than a preset second threshold value.
Preferably, in the above technical solution, the feature information in one or more video frames includes: the proportion of the field in the video frame, the proportion of the players in the video frame, the proportion of the referee in the video frame, the proportion of the forbidden region in the video frame, the proportion of the midfield region in the video frame, the proportion of the corner ball region in the video frame and the frame motion intensity.
Preferably, in the above technical solution, the video frame judgment threshold is generated by a machine learning method with supervised learning, where the video frame judgment threshold includes: the video frame comprises a video frame, a plurality of court areas, a plurality of player areas, a plurality of judge areas, a plurality of forbidden areas, a plurality of midcourt areas, a plurality of corner ball areas and a frame motion intensity threshold.
Preferably, in the above technical solution, the determining the category of the highlight event based on the comparison relationship between the feature information and the plurality of video frame judgment threshold values specifically includes: if the ratio of the corner ball area in the video frame is greater than the ratio threshold of the first corner ball area in the video frame, and the ratio of the field in the video frame is less than the ratio threshold of the first field in the video frame, judging the highlight event as a corner ball event; and if the proportion of the judges in the video frame is greater than the proportion threshold of the first judges in the video frame, and the frame motion intensity is greater than the frame motion intensity threshold, judging the wonderful event as a foul event.
Preferably, in the above technical solution, the determining the category of the highlight event based on the comparison relationship between the feature information and the plurality of video frame judgment threshold values further includes: if the proportion of the midfield area in the video frame is smaller than the proportion threshold of the first midfield area in the video frame, the proportion of the forbidden area in the video frame is larger than the proportion threshold of the first forbidden area in the video frame, and the proportion of the player in the video frame is larger than the proportion threshold of the player in the video frame, the wonderful event is judged as a pointball event.
The invention also provides a football wonderful video capturing system, which comprises: the device comprises a unit for capturing a first brightness change of a football video; a unit for starting to extract one or more video frames after the first brightness change when the first brightness change is larger than a preset first threshold value; a unit for performing image processing on the video frame to obtain a video frame after the image processing; means for obtaining feature information in one or more video frames based on the video frames after the image processing; a unit for presetting a plurality of video frame judgment threshold values; means for determining a category of the highlight event based on a comparison between the feature information and a plurality of video frame determination threshold values; a unit for recording the video after the first brightness change and capturing a second brightness change in the video after the first brightness change is recorded; and a unit for stopping recording the video when the second luminance variation is larger than a second threshold value set in advance.
Preferably, in the above technical solution, the feature information in one or more video frames includes: the proportion of the field in the video frame, the proportion of the players in the video frame, the proportion of the referee in the video frame, the proportion of the forbidden region in the video frame, the proportion of the midfield region in the video frame, the proportion of the corner ball region in the video frame and the frame motion intensity.
Preferably, in the above technical solution, the video frame judgment threshold is generated by a machine learning method with supervised learning, where the video frame judgment threshold includes: the video frame comprises a video frame, a plurality of court areas, a plurality of player areas, a plurality of judge areas, a plurality of forbidden areas, a plurality of midcourt areas, a plurality of corner ball areas and a frame motion intensity threshold.
Preferably, in the above technical solution, the unit for determining the category of the highlight event based on the comparison relationship between the feature information and the plurality of video frame judgment threshold values is further configured to: if the ratio of the corner ball area in the video frame is greater than the ratio threshold of the first corner ball area in the video frame, and the ratio of the field in the video frame is less than the ratio threshold of the first field in the video frame, judging the highlight event as a corner ball event; and if the proportion of the judges in the video frame is greater than the proportion threshold of the first judges in the video frame, and the frame motion intensity is greater than the frame motion intensity threshold, judging the wonderful event as a foul event.
Preferably, in the above technical solution, the unit for determining the category of the highlight event based on the comparison relationship between the feature information and the plurality of video frame judgment threshold values is further configured to: if the proportion of the midfield area in the video frame is smaller than the proportion threshold of the first midfield area in the video frame, the proportion of the forbidden area in the video frame is larger than the proportion threshold of the first forbidden area in the video frame, and the proportion of the player in the video frame is larger than the proportion threshold of the player in the video frame, the wonderful event is judged as a pointball event.
Compared with the prior art, the invention has the following beneficial effects: the current video capturing method is to capture and analyze video frames from the beginning of a video to the end of the video at any time. When the football game video with the length of more than 90 minutes is analyzed in the mode, the number of frames which can be analyzed in each game reaches more than thirteen thousand, and a series of complex processing such as image processing, transformation, edge detection and analysis, statistics and the like is carried out on each video frame. This would be a very large amount of computation for computers, if a corporate user wants to analyze football videos with the prior art method, each computer can only process 1-3 videos at one time due to the computation, if the user is a very large entity such as a central station, the videos he wants to process may be thousands of, which means that thousands of computers are invested in large amounts of money if he wants to process all videos in a short period of time. Such investment is unacceptable even for the center console. In order to solve the problems of the prior art, the invention provides a method for reducing the computation amount of a computer, wherein the computer does not process each video frame, but only records the brightness change of each video through a sensor, then judges whether the brightness change exceeds a threshold or not through the computer, and only when the brightness change exceeds the threshold, the video frame processing is started, and the processing amount in the process can be ignored. The method of the invention fundamentally overcomes the defect of overlarge calculated amount in the prior art.
Drawings
Fig. 1 is a flow chart of a video capture method according to the present invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
Example 1
Fig. 1 is a flow chart of a video capture method according to the present invention. As shown in fig. 1, a video capturing method according to a preferred embodiment of the present invention includes: step 101: capturing a first brightness change of a football video; step 102: when the first brightness change is larger than a preset first threshold value, one or more video frames after the first brightness change are extracted; step 103: performing image processing on the video frame to obtain a video frame after the image processing; step 104: obtaining feature information in one or more video frames based on the video frames after the image processing; step 105: presetting a plurality of video frame judgment threshold values; step 106: determining the category of the wonderful event based on the comparison relationship between the characteristic information and the plurality of video frame judgment threshold values; step 107: recording the video after the first brightness change, and capturing a second brightness change in the video after the first brightness change is recorded; and step 108: and stopping recording the video when the second brightness change is larger than a preset second threshold value.
Example 2
In a preferred embodiment, the feature information in one or more video frames comprises: the proportion of the field in the video frame, the proportion of the players in the video frame, the proportion of the referee in the video frame, the proportion of the forbidden region in the video frame, the proportion of the midfield region in the video frame, the proportion of the corner ball region in the video frame and the frame motion intensity. The video frame judgment threshold value is generated by a machine learning method with supervised learning, wherein the video frame judgment threshold value comprises the following steps: the video frame comprises a video frame, a plurality of court areas, a plurality of player areas, a plurality of judge areas, a plurality of forbidden areas, a plurality of midcourt areas, a plurality of corner ball areas and a frame motion intensity threshold.
Example 3
In another preferred embodiment, the determining the category of the highlight event based on the comparison relationship between the feature information and the plurality of video frame judgment threshold values specifically includes: if the ratio of the corner ball area in the video frame is greater than the ratio threshold of the first corner ball area in the video frame, and the ratio of the field in the video frame is less than the ratio threshold of the first field in the video frame, judging the highlight event as a corner ball event; and if the proportion of the judges in the video frame is greater than the proportion threshold of the first judges in the video frame, and the frame motion intensity is greater than the frame motion intensity threshold, judging the wonderful event as a foul event. Determining the category of the highlight event based on the comparison between the feature information and the plurality of video frame judgment threshold values further specifically comprises: if the proportion of the midfield area in the video frame is smaller than the proportion threshold of the first midfield area in the video frame, the proportion of the forbidden area in the video frame is larger than the proportion threshold of the first forbidden area in the video frame, and the proportion of the player in the video frame is larger than the proportion threshold of the player in the video frame, the wonderful event is judged as a pointball event.
Example 4
The invention also provides a football highlight video capture system, which comprises: the device comprises a unit for capturing a first brightness change of a football video; a unit for starting to extract one or more video frames after the first brightness change when the first brightness change is larger than a preset first threshold value; a unit for performing image processing on the video frame to obtain a video frame after the image processing; means for obtaining feature information in one or more video frames based on the video frames after the image processing; a unit for presetting a plurality of video frame judgment threshold values; means for determining a category of the highlight event based on a comparison between the feature information and a plurality of video frame determination threshold values; a unit for recording the video after the first brightness change and capturing a second brightness change in the video after the first brightness change is recorded; and a unit for stopping recording the video when the second luminance variation is larger than a second threshold value set in advance.
Example 5
In a preferred embodiment, the feature information in one or more video frames comprises: the proportion of the field in the video frame, the proportion of the players in the video frame, the proportion of the referee in the video frame, the proportion of the forbidden region in the video frame, the proportion of the midfield region in the video frame, the proportion of the corner ball region in the video frame and the frame motion intensity. The video frame judgment threshold value is generated by a machine learning method with supervised learning, wherein the video frame judgment threshold value comprises the following steps: the video frame comprises a video frame, a plurality of court areas, a plurality of player areas, a plurality of judge areas, a plurality of forbidden areas, a plurality of midcourt areas, a plurality of corner ball areas and a frame motion intensity threshold.
Example 6
In another preferred embodiment, the means for determining the category specificity of the highlight event based on a comparison between the feature information and the plurality of video frame determination threshold values is further configured to: if the ratio of the corner ball area in the video frame is greater than the ratio threshold of the first corner ball area in the video frame, and the ratio of the field in the video frame is less than the ratio threshold of the first field in the video frame, judging the highlight event as a corner ball event; and if the proportion of the judges in the video frame is greater than the proportion threshold of the first judges in the video frame, and the frame motion intensity is greater than the frame motion intensity threshold, judging the wonderful event as a foul event. The means for determining the category specificity of the highlight event based on a comparison between the feature information and a plurality of video frame determination threshold values is further configured to: if the proportion of the midfield area in the video frame is smaller than the proportion threshold of the first midfield area in the video frame, the proportion of the forbidden area in the video frame is larger than the proportion threshold of the first forbidden area in the video frame, and the proportion of the player in the video frame is larger than the proportion threshold of the player in the video frame, the wonderful event is judged as a pointball event.
Example 7
Apparatus and methods have been described in the detailed description and illustrated in the accompanying drawings by various elements including blocks, modules, components, circuits, steps, processes, algorithms, and so forth. These elements, or any portion thereof, may be implemented using electronic hardware, computer software, or any combination thereof, alone or in combination with other elements and/or functions. Whether such elements are implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. In one aspect, the term "component" as used herein may be one of the components that make up the system and may be divided into other components.
For example, an element or any portion of an element or any combination of elements may be implemented with a "system" that includes one or more processors. The processor may include a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic component, discrete gate or transistor logic, discrete hardware components, or any combination thereof, or any other suitable component designed to perform the functions described herein. A general purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing components, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP, or any other such configuration.
One or more processors in the system may execute the software. Software shall be construed broadly to mean instructions, instruction sets, code segments, program code, programs, subprograms, software modules, applications, software packages, routines, subroutines, objects, executables, threads of execution, procedures, functions, etc., whether referred to as software, firmware, middleware, microcode, hardware description language, or otherwise. The software may reside on a transitory or non-transitory computer readable medium. By way of example, a non-transitory computer-readable medium may include a magnetic storage device (e.g., hard disk, floppy disk, magnetic strips), an optical disk (e.g., Compact Disk (CD), Digital Versatile Disk (DVD)), a smart card, a flash memory device (e.g., card, stick, key drive), Random Access Memory (RAM), static RAM (sram), dynamic RAM (dram), synchronous dynamic RAM (sdram); double data rate ram (ddram), Read Only Memory (ROM), programmable ROM (prom), erasable prom (eprom), electrically erasable prom (eeprom), general purpose registers, or any other suitable non-transitory medium for storing software.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (2)
1. A football highlight video capturing method is characterized by comprising the following steps: the football highlight video capturing method comprises the following steps:
capturing a first brightness change of a football video;
when the first brightness change is larger than a preset first threshold value, one or more video frames after the first brightness change are extracted;
performing image processing on the video frame to obtain a video frame after the image processing;
obtaining feature information in the one or more video frames based on the video frames after the image processing;
presetting a plurality of video frame judgment threshold values;
determining the category of a highlight event based on the comparison relationship between the feature information and the plurality of video frame judgment threshold values;
recording the video after the first brightness change, and capturing a second brightness change in the video after the first brightness change is recorded; and
when the second brightness change is larger than a preset second threshold value, stopping recording the video, wherein the characteristic information in one or more video frames comprises: the video frame judgment threshold value is generated by a machine learning method with supervised learning, wherein the video frame judgment threshold value comprises: the method specifically comprises the following steps of determining the category of a highlight event based on the comparison relationship between the characteristic information and the video frame judgment threshold values, wherein the ratio threshold of a plurality of fields in a video frame, the ratio threshold of a plurality of players in the video frame, the ratio threshold of a plurality of referees in the video frame, the ratio threshold of a plurality of forbidden regions in the video frame, the ratio threshold of a plurality of midcourt regions in the video frame, the ratio threshold of a plurality of corner ball regions in the video frame and the frame motion intensity threshold value specifically comprises the following steps:
if the ratio of the corner ball area in the video frame is greater than the ratio threshold of the first corner ball area in the video frame, and the ratio of the field in the video frame is less than the ratio threshold of the first field in the video frame, judging the highlight event as a corner ball event; and
if the proportion of the referees in the video frames is greater than the proportion threshold of the first referees in the video frames, and the frame motion intensity is greater than the frame motion intensity threshold, judging the wonderful event as a foul event, and determining the category of the wonderful event based on the comparison relationship between the feature information and the plurality of video frame judgment threshold values further specifically comprises: if the proportion of the midfield area in the video frame is smaller than the proportion threshold of the first midfield area in the video frame, the proportion of the forbidden area in the video frame is larger than the proportion threshold of the first forbidden area in the video frame, and the proportion of the player in the video frame is larger than the proportion threshold of the player in the video frame, the wonderful event is judged as a pointcast event.
2. A soccer highlights video capturing system, comprising: the soccer highlights video capturing system comprises:
the device comprises a unit for capturing a first brightness change of a football video;
a unit for starting to extract one or more video frames after the first brightness change when the first brightness change is larger than a preset first threshold value;
a unit for processing the video frame to obtain a video frame after image processing;
means for deriving feature information in the one or more video frames based on the video frames after image processing;
a unit for presetting a plurality of video frame judgment threshold values;
means for determining a category of a highlight event based on a comparison between the feature information and the plurality of video frame determination threshold values;
a unit for recording the video after the first brightness change and capturing a second brightness change in the video after recording the first brightness change; and
a unit for stopping recording the video when the second brightness change is larger than a preset second threshold, wherein the feature information in the one or more video frames comprises: the video frame judgment threshold value is generated by a machine learning method with supervised learning, wherein the video frame judgment threshold value comprises: the unit for determining the type of the highlight event is further configured to:
if the ratio of the corner ball area in the video frame is greater than the ratio threshold of the first corner ball area in the video frame, and the ratio of the field in the video frame is less than the ratio threshold of the first field in the video frame, judging the highlight event as a corner ball event; and
if the proportion of the referees in the video frames is greater than the proportion threshold of the first referees in the video frames, and the frame motion intensity is greater than the frame motion intensity threshold, determining the highlight event as a foul event, and determining the category of the highlight event based on the comparison relationship between the feature information and the plurality of video frame determination threshold values, the unit is further configured to: if the proportion of the midfield area in the video frame is smaller than the proportion threshold of the first midfield area in the video frame, the proportion of the forbidden area in the video frame is larger than the proportion threshold of the first forbidden area in the video frame, and the proportion of the player in the video frame is larger than the proportion threshold of the player in the video frame, the wonderful event is judged as a pointcast event.
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| US10805579B2 (en) * | 2019-01-30 | 2020-10-13 | Primesensor Technology Inc. | Motion detection methods and motion sensors capable of more accurately detecting true motion event |
| CN110688498B (en) * | 2019-09-27 | 2022-07-22 | 北京奇艺世纪科技有限公司 | Information processing method and device, electronic equipment and storage medium |
| CN111001149B (en) * | 2019-12-10 | 2021-06-04 | 苏宁智能终端有限公司 | Position positioning method and system based on video playback |
| CN111787338A (en) * | 2020-03-09 | 2020-10-16 | 北京理工大学 | Auxiliary design method for sports event live broadcast scheme |
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