計算機視覺行業,這

The use of advanced CV or computer vision applications in sports ultimately allows for a highly efficient, fast, and precise analysis of actions, conditions, and environments in all possible sports events.

在運動中使用高級CV或計算機視覺應用程序最終可以在所有可能的體育賽事中對動作，狀況和環境進行高效，快速和精確的分析。

A naked human eye is being gradually replaced with smart algorithms that do all the cumbersome analytics automatically. These capacities may help better analyze the crucial sports event moments to get more precise scores and judge more efficiently as a whole.

肉眼已經逐漸被自動執行所有繁瑣分析的智能算法所取代。 這些能力可以幫助更好地分析關鍵體育賽事的時刻，從而獲得更精確的比分并從整體上更有效地進行判斷。

Although the use of CV in professional sports mostly requires pre-recorded content of high-definition, the technology is pretty in-depth efficient in processing video of any format, coming from any device. Where in particular this form of machine processing is applied? Let’s dive a bit deeper into the topic of using content processing via computer vision in the sports industry.

盡管在專業運動中使用CV大多需要預先錄制的高清內容，但該技術在處理來自任何設備的任何格式的視頻方面非常有效。 這種形式的機器處理特別適用于什么地方？ 讓我們更深入地探討體育行業中通過計算機視覺使用內容處理的主題。

通過簡歷有效分析共同時刻 (Common Moments Efficiently Analyzed via CV)

Besides the obvious use in the security systems most demanding for image quality (recognition of faces, dangerous objects, etc.), machine vision technologies are used in many other cases in sports:

除了在對圖像質量要求最高(識別人臉，危險物體等)的安全系統中有明顯用途外，機器視覺技術還用于體育運動中的許多其他情況：

• training process — the in-depth analysis of captured actions in swimming, gymnastics, athletics, skiing, and other sports where the technique of performing movements matters the most;
  訓練過程-深入分析在游泳，體操，田徑，滑雪和其他運動中技巧最為重要的運動中捕獲的動作；
• refereeing — 3D simulations and video inspection of the offsides, outs, goals, photo finish in mass races; all;
  裁判員-群眾比賽中越位，出球，進球，照片完成的3D模擬和視頻檢查； 所有;
• the rates of player activity during events — for instance, in tennis, the dynamics of players can be captured and analyzed based on their movements and even slight gestures;
  運動員在比賽中的活動率，例如在網球比賽中，可以根據運動員的動作甚至輕微的手勢來捕獲并分析運動員的動態；
• ball (puck, you name it) trajectories — these can be analyzed as well as predicted for further in-depth analytics;
  球(圓盤，您叫它)軌跡-可以對這些軌跡進行分析和預測，以進行進一步的深入分析；
• action camera stabilization and smart focus — artificial intelligence in sports allow for real-time smoothing out of action frames and automated focus based on the density of activity and target actions in the field.
  動作相機穩定和智能對焦-運動中的人工智能可根據動作密度和現場目標動作實時平滑動作框架并自動對焦。

These are just some general capabilities modern sports events organizers get to employ. Let’s take a look at a bunch of particular cases in a bit greater detail.

這些只是現代體育賽事組織者可以使用的一些常規功能。 讓我們更詳細地看一堆特殊情況。

計算機視覺在體育中的應用 (Computer Vision Applications in Sports)

曲棍球中的實時動作識別(Real-time action recognition in hockey)

Specialists at the Shiraz University and the University of Waterloo did a whole paper on efficient recognition of actions in hockey. The main gist is that experts have come up with the so-called Action Recognition Hourglass Network (ARHN), which is a complex, multi-component visual data processing model.

設拉子大學和滑鐵盧大學的專家撰寫了一篇有關有效識別曲棍球動作的論文。 主要要點是專家提出了所謂的動作識別沙漏網絡(ARHN)，這是一個復雜的，多組件的可視數據處理模型。

In simple terms, the complex algorithm takes a piece of motion video content and converts it into a series of images. Another underlying algorithm within a Stacked Hourglass network then analyzes players’ positions (straight and crossover skating, pre- and post-shot poses) and classifies them.

簡而言之，復雜的算法獲取一段運動視頻內容，并將其轉換為一系列圖像。 然后，Stacked Hourglass網絡中的另一種基礎算法將分析運動員的位置(直線和交叉溜冰，鉛球前后姿勢)并對其進行分類。

These models have been used for the longest time to help issue the fairest, most precise scores in this and other types of sports out there.

這些模型已經使用了最長的時間，以幫助在這種運動和其他類型的運動中發布最公平，最精確的分數。

網球中的球追蹤系統 (Ball tracking systems in tennis)

Precise tennis (as well as badminton and cricket) ball trajectories have been tracked in sports since the mid-2000s. Thus, specialized systems focus on multiple objects in the image that are similar in form to a ball. Upon detecting these, a 3-dimensional trajectory is built by connecting the ball movement pattern frame by frame.

自2000年代中期以來，人們一直在運動中追蹤精確的網球(以及羽毛球和板球)的運動軌跡。 因此，專用系統專注于圖像中形式類似于球的多個對象。 一旦檢測到這些，就通過一幀接一幀地連接球運動圖案來建立3維軌跡。

This is where multiple camera angles and flexible motion capture are essential. The main purpose here is the precise statement on whether the ball landed in or out of bounds during the game. On their deepest, most complex layers, the underlying algorithms can build predictions of ball trajectories based on various conditions (a player’s miss or such).

在這里，多個攝像機角度和靈活的運動捕捉至關重要。 這里的主要目的是在比賽過程中準確地說明球是落入還是出界。 在最深，最復雜的層上，基礎算法可以根據各種條件(球員的失誤等)建立對球軌跡的預測。

Based on such solutions, smart statistics are generated in real-time for 100% fair refereeing and reputable sports performance analytics.

基于此類解決方案，可以實時生成智能統計信息，以實現100％公平裁判和聲譽卓著的體育表現分析。

培訓活動分析 (Training activities analytics)

Modern sport imposes higher demands not only on the athletes but also on the team of coaches. The key advantage in team sports is not so much the presence of “stars” as the proper organization of the team game, the assessment of the actions of each player, their interaction, and it is invaluable for the coach to develop effective tactics and game strategies.

現代運動不僅對運動員而且對教練團隊都提出了更高的要求。 團隊運動的主要優勢不在于“明星”的存在，而在于團隊比賽的正確組織，對每個球員的動作的評估，他們之間的互動，并且教練制定有效的戰術和比賽是無價的策略。

Computer vision in sports analytics is a great tool for getting objective, up-to-date information in the conditions when just recording a video of a game field is not enough. Mathematical processing of the video stream allows getting the position of each player of opponents’ teams at each moment.

運動分析中的計算機視覺是在僅記錄比賽視頻的條件下，獲取客觀，最新信息的絕佳工具。 視頻流的數學處理使您可以隨時獲取對手團隊中每個球員的位置。

For many sports arenas and clubs, sports video analytics systems have now become a very profitable business. Even though the creation of such systems requires organizing the synchronous operation of dozens of cameras and powerful computing capabilities, the effort is usually well paid off in the long run.

對于許多體育館和俱樂部而言，體育視頻分析系統現已成為一項非常有利可圖的業務。 即使創建這樣的系統需要組織數十臺攝像機的同步操作和強大的計算功能，但從長遠來看，通常可以很好地獲得回報。

預防威脅生命的情況 (Prevention of life-threatening situations)

In NASCAR racing and similar kinds of sports where players experience potential life dangers, computer vision is used to timely detect and prevent vehicle malfunctions. This is where such systems, basically, save lives.

在NASCAR賽車和類似運動中，玩家可能面臨生命危險，計算機視覺可用于及時發現和防止車輛故障。 基本上，這就是這些系統挽救生命的地方。

Commonly, huge Big Data-based databases of vehicle models are implemented to recognize particular cars, analyzing them in the tiniest detail during the event. Thus, experts get real-time reach into the car’s insides to track any small malfunctions which can lead to serious consequences.

通常，會基于大型的基于大數據的車輛模型數據庫來識別特定的汽車，并在活動期間以最小的細節對其進行分析。 因此，專家可以實時進入汽車內部，以追蹤可能導致嚴重后果的任何小故障。

For many sports arenas and clubs, sports video analytics systems have now become a very profitable business. Even though the creation of such systems requires organizing the synchronous operation of dozens of cameras and powerful computing capabilities, the effort is usually well paid off in the long run.

對于許多體育館和俱樂部而言，體育視頻分析系統現已成為一項非常有利可圖的業務。 即使創建這樣的系統需要組織數十臺攝像機的同步操作和強大的計算功能，但從長遠來看，通常可以很好地獲得回報。

粉絲情緒和參與度分析 (Fan mood and engagement analysis)

A not so obvious application of a machine learning in sports analytics — organizers can recognize faces on the tribunes and identify emotions fans experience. This is made to stimulate the hype on the tribunes and build statistics on fan engagement as well as an event’s overall impact.

機器學習在體育分析中的應用不是那么明顯-組織者可以識別論壇上的面Kong并識別球迷的情感體驗。 這樣做是為了刺激對論壇的炒作，并建立有關粉絲參與度以及賽事整體影響的統計數據。

智慧體育新聞 (Smart sports journalism)

Adding up to the previous point and expanding on the influence of a sports event on fans. Computer vision can also be beneficially used to generate impressive media content and more precisely report on the game highlights.

結合上一點，擴大體育賽事對球迷的影響。 計算機視覺還可以有益地用于生成令人印象深刻的媒體內容，并更精確地報告游戲亮點。

By analyzing the most standing-out, dynamic actions happening in the field (track, ring, etc.) based on some above-mentioned algorithms, an immediate focus on the most exciting happenings can be employed.

通過基于上述某些算法分析現場(軌道，環等)中最突出的動態動作，可以立即關注最激動人心的事件。

This is a crucial capability when it comes to live events to help keep all spectators on the edge of their seats. And apart from visual features, AI even helps to automatically commentate events without the help of live speakers (Automated Insights, for instance, developed a solution for real-time narratives based on Natural Language Recognition capacities).

當涉及現場比賽時，這是一項至關重要的功能，可幫助所有觀眾保持座位邊緣。 除了視覺功能外，人工智能甚至可以幫助自動注釋事件，而無需現場演講者的幫助(例如，自動洞察為基于自然語言識別能力的實時敘事開發了解決方案)。

體育計算機視覺軟件的特點 (The Specifics of Software for Computer Vision in Sports)

The above applications and more make the world of sports a firmly-watched, ever so exciting, and fair competitive realm to organize. There are various types of solutions in the niche. Some of the leading examples include Sentio’s smart tracking and analytics systems; Stats Perform’s SportVU 2.0 with in-depth computer vision-based algorithms; GAMEFACE.AI with its in-depth analysis of strategic insights and other footage points; and more.

上述應用程序以及更多應用程序使體育界成為一個備受關注的，令人興奮的，公平的競爭領域。 利基市場中有各種類型的解決方案。 一些領先的例子包括Sentio的智能跟蹤和分析系統。 Stats Perform的SportVU 2.0具有基于計算機視覺的深度算法； GAMEFACE.AI具有對戰略見解和其他鏡頭的深入分析； 和更多。

The available solutions are intricate systems to be integrated through hardware and software by a dedicated integrator specialist. The role of the integrator is limited to adapting the system based on the readymade standard components according to the requirements of a particular customer, its binding to a specific object, installation, and service entry.

可用的解決方案是復雜的系統，由專門的集成商專家通過硬件和軟件進行集成。 集成商的作用僅限于根據特定客戶的需求，基于與特定對象的綁定，安裝和服務條目，基于現成的標準組件來調整系統。

Thus, the resolution and speed of the cameras are limited by the capabilities of the human operator, and the main focus is made on minimizing the volume of video recordings and the convenience of working with them.

因此，攝像機的分辨率和速度受到操作人員能力的限制，并且主要重點在于使視頻記錄的體積最小化以及使用它們的便利性。

獲得最高質量分析的關鍵點 (Crucial points for getting the highest-quality analytics)

The industry of computer vision system for tracking players in sports games has slightly different priorities arising from a much wider range of tasks, which cause a very limited distribution and use of “boxed” products. Due to the diversity of objects and tasks for observation, the requirements for image capture systems vary greatly.

跟蹤運動游戲中的運動員的計算機視覺系統行業由于任務范圍廣泛而導致優先級略有不同，這導致“盒裝”產品的分配和使用非常有限。 由于觀察對象和任務的多樣性，對圖像捕獲系統的要求差異很大。

First of all, it’s supposed to be machine image processing, which entails requirements for the maximum transfer of details, diversity, and uniformity of shooting conditions to increase the efficiency (showing details), speed, and reliability (shooting conditions) of the algorithms. Based on our team’s experience, the main points in the selection of machine vision components are as follows:

首先，它應該是機器圖像處理，它要求最大程度地傳遞細節，多樣性和拍攝條件的一致性，以提高算法的效率(顯示細節)，速度和可靠性(拍攝條件)。 根據我們團隊的經驗，選擇機器視覺組件的要點如下：

• image quality, degree of detail, and speed (frame rate) must correspond to the mathematical algorithms used to solve various applied tasks;
  圖像質量，細節程度和速度(幀速率)必須與用于解決各種應用任務的數學算法相對應；
• lighting conditions should be as stable and/or controlled as much as possible. In most cases it’s artificial lighting;
  照明條件應盡可能穩定和/或控制。 在大多數情況下是人工照明。
• limited use or complete absence of automated functions such as auto exposure or autofocus in the camera. Everything is controlled by external software;
  相機使用受限或完全沒有自動功能(例如自動曝光或自動對焦)。 一切都由外部軟件控制；
• the main information processing is performed on separate calculators since the complexity of the algorithms does not allow placing the required computing power in a compact camera body. In some cases, joint processing of images from multiple cameras is required. The type and power of the calculator are determined by the requirements of the specific task and the math used;
  由于算法的復雜性不允許將所需的計算能力放在緊湊的相機機身中，因此主要信息處理是在單獨的計算器上執行的。 在某些情況下，需要對來自多個攝像機的圖像進行聯合處理。 計算器的類型和功能由特定任務的要求和所使用的數學確定；
• high-speed interfaces for transmitting images with high resolution (details) and high frame rate (fixing fast processes) are required;
  需要高速接口以高分辨率(細節)和高幀頻(固定快速處理)傳輸圖像；
• software functionality from camera manufacturers is limited to a set of drivers for the flexible configuration of equipment. We develop application programs for each specific project.
  相機制造商提供的軟件功能僅限于一組驅動程序，以實現設備的靈活配置。 我們為每個特定項目開發應用程序。

結論 (Conclusion)

Artificial intelligence in sports makes refereeing, analyzing, highlighting, and satisfying fans easier to grasp and more efficient in the long run. When it comes to implementing an AI-based system for sports events, you have the ultimate choice of going for renowned yet costly solutions or ordering a cost-efficient custom local system.

從長遠來看，體育運動中的人工智能使裁判，分析，重點關注和滿足球迷的需求更加容易，效率更高。 當要為體育賽事實施基于AI的系統時，您最終可以選擇采用著名但昂貴的解決方案，或訂購具有成本效益的定制本地系統。

Originally published at https://requestum.com.

最初發布在https://requestum.com 。

翻譯自: https://medium.com/quick-code/use-cases-of-computer-vision-in-the-sports-industry-ad190b33fbd1

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