This saves costs and allows human workforces to focus to higher value tasks. Amazon Rekognitionの概要 Amazon Rekognition は、AWSで画像分析とビデオ分析が利用できるサービスです。 Rekognition API に画像やビデオを指定するだけで、モノ、人物、テキスト、シーン、アクティビティを識別することができます。 Amazon Rekognition puede analizar los videos almacenados en Amazon S3 o los videos en directo de Kinesis Video Streams. Using Amazon Rekognition Video, you can break down this source content into its constituent shots, making it easy to choose the best clips for your final edited version. By detecting the SMPTE color bars and the beginning of end credits, you can clean up programs for streaming or add interactive user prompts such as ‘Next Episode’ when the end credits start rolling. Amazon Rekognition Video は、ストリーミング動画の リアルタイムの分析と顔分析を提供する使いやすい API を提供します。この完全管理の APIドライブによるサービスは、開発者が既存のアプリケーションに視覚分析を容易に追加することを Learn more about Amazon Rekognition pricing. rekognition-video-utils Reference implementation on labeling video frames using Amazon Rekognition. With Amazon Rekognition Video, you can detect such black frame sequences to automate ad insertion, package content for VOD, and demarcate various program segments or scenes. You can leverage Amazon Rekognition Video to prepare archived and third-party content for VOD workflows. Amazon Rekognition có thể phân tích các video được lưu trữ trong Amazon S3 hoặc phát trực tiếp video từ Kinesis Video Streams. Shot metadata can be used for applications such as creating promotional videos using selected shots, generating a set of preview thumbnails that avoid transitional content between shots, and inserting ads in spots that don’t disrupt viewer experience, such as the middle of a shot when someone is speaking. © 2021, Amazon Web Services, Inc. or its affiliates.All rights reserved. A+E Networks® is a collection of culture brands that includes A&E®, HISTORY®, Lifetime®, LMN™, FYI™, Vice TV and BIOGRAPHY®. Note The Amazon Rekognition Video streaming API is available in the following regions only: US East (N. Virginia), US West (Oregon), Asia Pacific (Tokyo), EU (Frankfurt), and EU (Ireland). Amazon Rekognition Video makes it easy to automate these operational media analysis tasks by providing fully managed, purpose-built APIs powered by ML. Lưu trữ siêu dữ liệu về khuôn mặt: Để có thể tìm kiếm khuôn mặt, bạn sẽ cần lưu trữ một kho siêu dữ liệu khuôn mặt mà dựa theo đó, Amazon Rekognition … Developers can quickly take advantage of different APIs to identify There are no minimum fees, licenses, or upfront commitments. Amazon Rekognition Video enables you to create reliable and easy to use media operations workflows in the cloud without upfront commitments or expensive licenses for on-premise software. [AWS マネジメントコンソール] を開きます。この作業手順ガイドは開いたままにしておいてください。この画面が読み込まれたら、ユーザー名とパスワードを入力して、作業を開始します。次に検索バーに Rekognition と入力し、サービスコンソールを開けるために Rekognition を選択します。, 本ステップでは、Rekognition Video コンソールを操作し、Rekognition API を通して利用可能な各機能の能力を理解することになります。, a) 開始するにあたり、左側のパネルナビゲーションで Video analysis を選択します。これにより、動画を分析すること、および JSON 応答を受け取ることができます。, b) あらかじめアップロードされた Jeff Bezos と Werner Vogels の動画は、Rekognition Video がいかにして人々を追跡できるか、いかに行動を検知し、いかに対象物や有名人、不適切なコンテントを認知できるかを実演します。, c) 最初に People の下、 Werner Vogels のアイコンをクリックします。そうすると画面右側の動画は、Werner が登場するクリップを映し出します。, d) 次に、この短いクリップで検出されたオブジェクトとアクティビティを確認します。Beard をクリックして Werner のあごひげが検知された正確な時間を確認する、あるいは Furniture をクリックしていつ椅子が検出されたのかを確認できます。, e) また、moderated labelsが全く見つからないことも見て取れます。本機能は、お客様の判断にて不適切なコンテンツにフィルターをかけることを可能にします。例えば、お客様はヌードを含む画像にフィルターをかけたいかもしれませんが、それを連想させる内容の画像にはフィルターをかけたくないかも知れません。, 本ステップでお客様には、チュートリアルのこの箇所で使用されることになる 30 秒の動画 1 本をダウンロードして頂き、それを分析するために Rekognition コンソールにアップロードして頂く事になります。, b) Choose a sample または upload your own の下にある下向きの矢印をクリックして、Your own video をクリックし、ビデオ映像を選択してお客様のデスクトップに保存します。コンソールにて無料デモを流すに当たり、動画ファイルは、60 mb または 60 秒を超えてはならない点をご注記下さい。, 40 ～ 50 秒後、動画が分析され、その結果がコンソールにて見られるようになります。, c)Rekognition がクリップから 12 名を検出したことに注目します。例えば、People 下の Show more をクリックし、オレンジと黒の縦縞シャツを着たレフリーを選択します。この特定のレフリーがビデオにて検知された時に右側の動画分析にて見ることができます。, d)Objects and activitiesをクリックします。自動的にタグが付けられた 20 の物体およびアクティビティがあることに注目します。例えば Automobile をクリックして 一台の自動車が検出された動画の各シーンを閲覧します。, e) 次に、Team Sportをクリックして、右手の動画分析におけるフラッグが立てられた各クリップが、本ステップを通じて選択してきたラベルの内少なくともひとつを含むことになることに注目します：レフリーは People 、そして自動車は Object、Team Sport は Activity の下に帰属します。, 開発者としてビデオ映像からの自動メタデータは、マーケティングや広告活動を改善させ、検索可能な動画ライブラリの構築、またはスポーツ競技に豊かな分析を提供するスポーツトラッキングを立ち上げるためのアプリケーションにおいて使用できる可能性があります。, b) お客様がアップロードされた動画は、ひとつの S3 bucket に自動的に保存されますので、費用を発生させないためお客様は、それを消去する必要があります。スクロールをして S3 buckets に目を通して 　rekognition-video-console-demoで始まる bucket を見つけます。この bucket およびselect all mediaをクリックして、次に右クリックをしDeleteを選択します。, お客様は、動画を分析するための Rekognition console の使用方法を学習したことになります。お客様は、大きなスケールで運用することができるように、Rekognition APIs を使用して本機能を実行することもできます。お客様が、検索可能なライブラリを構築し、あるいは行方不明者または VIP を見つけるためのアプリケーションの作成、安全でない動画を検出する必要がある場合、Amazon Rekognition Video を使用します。, この 開発者ガイド を使って Amazon Rekognition の機能について詳しく学習する。, 自動顔認識などのエンドツーエンドのメディア分析ソリューションを構築する方法をご確認ください。, 有名人認識や画像モデレーションなど、その他の Amazon Rekognition 機能を詳しく見る。. Through the Amazon Rekognition API , enterprises can enable their applications to detect and analyze scenes, objects, faces and other items within images. Amazon Rekognition is a machine learning based image and video analysis service that enables developers to build smart applications using computer vision. Viewers are watching more content than ever. 前回のAmazon Rekognitionをさわってみた その1の続きです。今回は、AWSのサービスと連携して、Amazon Rekognitionを使ってみました。 With the rich metadata returned by Amazon Rekognition Video, you can easily scale and automate manual operational tasks such preparing content for VOD, inserting ads and creating ‘binge-friendly’ prompts such as skipping to the next episode when end credits start rolling. Amazon Rekognition Video can also monitor a live stream that you create from Amazon Kinesis Video Streams to detect and search faces from face data that you provide. Amazon's Rekognition has been controversial, but it's also used for a wide variety of useful things. Today, companies use large teams of trained human workforces to perform tasks such as finding where the end credits begin in a piece of content, choosing the right spots to insert ads, or breaking up videos into smaller clips for better indexing. A shot is a series of interrelated consecutive pictures taken contiguously by a single camera and representing a continuous action in time and space. This metadata is useful to prepare content for VOD applications by removing color bar segments from the content, or to detect issues such as loss of broadcast signals in a recording, when color bars are shown continuously as a default signal instead of content. このセクションでは、Amazon Rekognition API オペレーションについて説明します。 「翻訳は機械翻訳により提供されています。提供された翻訳内容と英語版の間で齟齬、不一致または矛盾がある場合、英語版が優先します。 You can use Amazon Rekognition Video to detect timecodes of ad insertion markers (a series of black frames with silence) or suitable ad insertion spots (at shot change boundaries). With this metadata, you can then use services like AWS Elemental MediaTailor to stich ads seamlessly into your content. Amazon Rekognition Video’s media analysis features provide frame accurate detection results along with SMPTE timecodes. Promomii is an AI powered video logging and promo generation software company that helps creatives maximize the potential of their videos. © 2021, Amazon Web Services, Inc. or its affiliates. Amazon Rekognition Video allows you to detect sections of video that display SMPTE color bars, which are a set of colors displayed in specific patterns to ensure color is calibrated correctly on broadcast monitors, programs, and on cameras. Returned SMPTE timecodes are frame accurate, which means that Amazon Rekognition Video provides the exact frame number when it detects a relevant segment of video, and handles various video frame rate formats under the hood. Amazon Rekognition Video provides an easy to use API that identifies useful segments of video such as color bars and end credits. Amazon Rekognition Video provides a stream processor (CreateStreamProcessor) that you can use to start and manage the analysis of streaming video. Nomad is a cloud-native intelligent content management platform built on AWS serverless architecture, which seamlessly merges content and asset management with the power of AI/ML into one unified system. This enables you to perform tasks such as content preparation, ad insertion, and adding ‘binge-markers’ to content at scale in the cloud. But most people might not know what the service actually does. These manual processes are expensive, slow, and cannot scale to keep up with the volume of content being produced, licensed, and retrieved from archives daily. Synchronized transforms passive, linear video into ‘Smart-Video’. With proliferating content volumes, media companies are facing challenges in preparing and managing content, which are crucial to providing a high-quality viewing experience and better monetizing content. Almacenamiento de metadatos de rostros: Para habilitar la búsqueda de rostros, deberá almacenar un repositorio de metadatos de rostros en el que Amazon Rekognition … I then asked Amazon to look for faces in a short selfie video, then requested find a photo match. Q: Why is this project titled "amazon-rekognition-video-analyzer" despite the security-focused use case? We are in seven out of 10 American homes, cumulatively reach 335 million people worldwide and have 500+ million digital users. With this information, you can generate markers for interactive viewer prompts such as ‘Next Episode’ in VOD applications, or find out exactly where program contents end in a video. Amazon Rekognition Video helps you automatically identify the exact frame where the end credits start for a movie or TV show. With Amazon Rekognition Video, you pay only for what you use. Amazon Rekognition Video is trained to handle a wide variety of end credit styles ranging from simple rolling credits to more challenging credits alongside content, and can exclude intro credits automatically. 保存したビデオで Amazon Rekognition Video API を使用するには、IAM ユーザーと IAM サービスロールを設定して Amazon SNS トピックにアクセスする必要があります。また、Amazon SQS キューを Amazon SNS トピックにサブスクライブ With Amazon Rekognition Video, you can detect the start, end, and duration of each shot, as well as account for all the shots in a piece of content. Viewers are watching more content than ever, with Over-The-Top (OTT) and Video-On-Demand (VOD) platforms in particular providing a rich selection of content choices anytime, anywhere, and on any screen. You simply pay based on the duration of video that is processed and the features you use. Again, quick success with another 99% match. The repo also contains some OpenCV based video utilities for frame extraction and labeling. Amazon Rekognition Video’s media analysis features provide frame accurate detection results along with SMPTE timecodes. Dependencies OpenCV You can incorporate audio analysis such as closed captioning, profanity filtering and streaming video transcription into your applications by using Amazon Transcribe along with Amazon Rekognition Video. Black frames with audio (such as fade outs or voiceovers) are considered as content and not returned. Click here to return to Amazon Web Services homepage, Analyze videos with Media Insights Engine, Amazon Rekognition Custom Labels Features. Amazon Rekognition では、イメージ分析とビデオ分析をアプリケーションに簡単に追加することができます。Amazon Rekognition API にイメージやビデオを指定するだけで、このサービスによってモノ、人物、テキスト、シーン、アクティビティを識別できます。 In particular, Over-The-Top (OTT) and Video-On-Demand (VOD) platforms provide a rich selection of content choices anytime, anywhere, and on any screen. Amazon Rekognition Video free tier covers Label Detection, Content Moderation, Face Detection, Face Search, Celebrity Recognition, Text Detection and Person Pathing. Videos often contain a short duration of empty black frames with no audio that are used as cues to insert advertisements, or to demarcate the end of a program segment such as a scene or the opening credits. Our artificial intelligence engine understands the content and context of a video and enriches it with metadata. In the production of movies, shows and promotional videos, editors work with large volumes of footage. A: Although this prototype was conceived to address the security monitoring and alerting use case, you can use the prototype's architecture and code as a starting point to address a wide variety of use cases involving low-latency analysis of live video frames with Amazon Rekognition. このチュートリアルでは、AWS コンソールを使って、Amazon Rekognition Video の動画分析機能を使用する方法について学習します。Amazon Rekognition Video は、活動を検知したり、オブジェクト、有名人、および不適切なコンテンツを認識したりする、ディープラーニングを使用した動画分析サービスです。, 動画分析は、お客様が一開発者としてある動画カタログシステムを開発したり、あるいはセンチメント分析を提供するためのアプリを制作している場合に直面するひとつの課題です。この課題は、独自の機械学習モデルを構築することで解決できますが、このやり方は時間集約型かつ高価となり、機械学習の専門知識を必要とします。, Amazon Rekognition Video は、ストリーミング動画の リアルタイムの分析と顔分析を提供する使いやすい API を提供します。この完全管理の APIドライブによるサービスは、開発者が既存のアプリケーションに視覚分析を容易に追加することを可能にします。, 本チュートリアルでは、Amazon Rekognition Video を使用して、Ultimate Frisbee ゲームの 30 秒のクリップを分析します。動画を分析すると、リッチメタデータを自動的に抽出し、検索可能な動画ライブラリの構築、コンテンツのモデレーションの実行、またはパーソナライズされた VIP エクスペリエンスの提供のために使用することができます。, 本チュートリアルは、AWS CLI または Rekognition APIを使用する際に利用可能な機能のデモです。本番環境またはPoC (概念実証) の実施に関しては、Amazon Rekognition Console よりもむしろこれらのプログラマティックインターフェイスを使用することをお勧めします。, Amazon Rekognitionは追加料金なしで使用できます。お客様が本チュートリアルにおいて制作されたリソースは、 無料利用枠の対象となります。, a. All rights reserved. Amazon Rekognition Video: ディープラーニングベースのビデオ認識 【速報】Amazon Rekognition Videoが登場！ #reinvent さて、僕はこれまでAmazon Rekognitionを様々な不適切コンテンツに利用してきました。 Amazon Rekognitionの はじめに 先日AWS re:Invent 2017で発表されたAmazon Rekognition VideoとAmazon Kinesis Video Streams。今回はRekognitionのドキュメントにあるWorking with Streaming Videosに則って、Amazon Kinesis Video Streamsの映像をAmazon Rekognition Videoで解析してみたいと思います。 Using the frame accurate metadata from Amazon Rekognition Video, you can either automate certain tasks completely, or significantly reduce the review workload of trained human operators, so that they can focus on more creative work. Amazon Rekognition is an image analysis service available in the Amazon AI suite. This means that you get the exact frame number when Amazon Rekognition Video detects a specific type of video segment such as end credits. アマゾン ウェブ サービス（AWS）は動画の中の顔や動作を分析できる「Amazon Rekognition Video」など、深層学習を活用した複数のサービスを発表した。 Further, this service automatically handles integer, fractional and drop frame rate formats. This metadata then frees the video from linearity making it fully interactive and as powerful as hypertext to meet the demands and expectations of the digital world. Streamline quality control, ad insertion, and content production using machine learning. Using these APIs, you can easily analyze large volumes of videos stored in Amazon S3, detect markers such as black frames or shot changes, and get SMPTE (Society of Motion Picture and Television Engineers) timecodes and timestamps for each detection - without requiring any machine learning experience. Compare Amazon Rekognition vs Azure Custom Vision Service in Image Recognition Software category based on features, pricing, support and more RECENT SEARCHES Outs or voiceovers ) are considered as content and not returned cumulatively reach 335 million people worldwide and have million. A single camera and representing a continuous action in time and space you can then use Services like AWS MediaTailor... The repo also contains some OpenCV based video utilities for frame extraction and.... Using machine learning based image and video analysis service that enables developers to smart! Are considered as content and not returned end credits start for a movie or TV show no minimum fees licenses! Accurate detection results along with SMPTE timecodes 500+ million digital users its affiliates that is processed the! Into ‘ Smart-Video ’ are in seven out of 10 American homes, cumulatively reach 335 million people and... 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