Video Analysis, or Video Content Analysis (VCA), is a facet of Artificial Intelligence that utilizes machine learning formulas to analyze and comprehend video data. VCA involves scrutinizing, interpreting and distilling information from video footage for numerous uses.
This procedure can be done mechanically or by hand and is extensively used in many industries, such as surveillance, sports, entertainment, medical research and transportation. You can choose between several Video Analysis functionalities to meet your needs such as object detection, object tracking, face detection, people tracking, text detection, explicit content detection and logo detection.
In Video Analysis, videos are usually evaluated to extract significant details, such as things, scenes, and happenings, which are subsequently examined for insights, decision-making, or pattern recognition.
For instance, in sports, footage of a game can be scrutinized to follow a player's movements and strategies, evaluate their performance, and highlight areas for improvement. In surveillance, video analysis has the ability to uncover and trail doubtful actions, observe crowd movements, and aid investigations.
For users seeking a cost-effective engine, opting for an open-source model is recommended. Here is the list of the best Video Analysis Open Source Models:
This is an open source model for video analysis.
OpenPose is the initial real-time multi-person system to simultaneously spot 135 key points of the human body, hands, face, and feet on single images. It can be used for tasks like pose estimation, facial landmark detection, and hand tracking.
This repository has code for Basic Online and Real-time Tracking using a Deep Association Metric (Deep SORT). We added appearance information integration using a deep appearance descriptor to the original SORT algorithm.
This is a video analysis open source model created by Facebook. DensePose is a scheme for computing detailed human posture. It can decipher the pose of people in images and videos.
OpenCV is a popular library for computer vision. It has tools to analyze video like tracking objects, analyzing motion, and changing video. This library is vast and can handle many different tasks related to computer vision.
While open source models offer many advantages, they also have potential drawbacks and challenges. Here are some cons of using open source models:
Given the potential costs and challenges related to open-source models, one cost-effective solution is to use APIs. Eden AI smoothens the incorporation and implementation of AI technologies with its API, connecting to multiple AI engines.
Eden AI presents a broad range of AI APIs on its platform, customized to suit your specific needs and financial limitations. These technologies include data parsing, language identification, sentiment analysis, logo recognition, question answering, data anonymization, speech recognition, and numerous other capabilities.
To get started, we offer free $10 credits for you to explore our APIs.
Our standardized API enables you to integrate VCA APIs into your system with ease by utilizing various providers on Eden AI. Here is the list (in alphabetical order):
Amazon Rekognition Video provides various video analysis functions, such as recognizing faces, detecting objects and scenes, identifying text, and recognizing famous people.
Google Cloud Video Intelligence is a favorite for businesses that need rapid video analysis as it processes videos quickly and provides live video stream analysis. Shot detection, object tracking, and speaker diarization are among its sophisticated features.
Eden AI offers a user-friendly platform for evaluating pricing information from diverse API providers and monitoring price changes over time. As a result, keeping up-to-date with the latest pricing is crucial. The pricing chart below outlines the rates for smaller quantities for November 2023, as well as you can get discounts for potentially large volumes.
Eden AI is the future of AI usage in companies: our app allows you to call multiple AI APIs.
You can see Eden AI documentation here.
The Eden AI team can help you with your Video Content Analysis integration project. This can be done by :