Real-Time Video Processing: Everything Important That You Should Know
There are various industries such as entertainment, healthcare, security, and social media where video processing has become an integral component. However, the real-time video processing, that has recently captivated a great deal of interest owing to its more functional capabilities, allowing for the real-time processing of video streams. Since it allows for the effective processing of video in real-time for purposes such as object detection, video streaming, and communication, the real-time video processing markets are growing exponentially.
In today’s blog we are going to cover a wide range of topics related to real-time video processing, from the basics to the more complex subjects such as what applications can be developed with it, what the challenges it entails and how its built. We will also look at how video is encoded, decoded, streamed and analyzed and what are some case studies and what the future holds for this field.
Table of Contents
- Real-Time Video Processing Overview
- What is Real-Time Video Processing?
- The Significance of Processing in Real Time
- Main Building Blocks in Real-Time Video Processing Solutions
- A Physics Perspective on Video: Using the Medium and Its Mechanics
- Video Compression and Encoding
- Video Decoding
- Frame Rate and Resolution
- Real Time Video Processing Core Technologies
- Real Time Video Processing Hardware
- Software Development Kits and APIs
- Cloud and Edge Computing
- Video Processing with AI and ML
- Use Cases of Real-Time Video Processing
- Video-on-Demand Services
- Video Securitisation
- The Uses of Augmented and Virtual Reality
- Medical Diagnosis and Treatment
- Self-driving Cars
- Real-Time Video Processing Hurdles
- Delays and Bandwidth Capacity
- Data Loss and Corruption
- Hardware Limitations
- Power Usage
- Expandability
- Improving Real-Time Video Processing Workflows
- Ways to Compress Data
- GPU parallelization
- Low Latency Protocols
- Distributed and Edge Systems
- Future Trends and Innovations
- Mobile Network Technology: From 5G and Further Onwards
- Video Processing Intervention with AI tools and applications
- The Use of Blockchain in Video Streaming Domain
- Video Communication Without Delay-Does it Navigate into the Future?
- Conclusion
1. Introduction to Real-Time Video Processing
Real-Time Video Processing: Definition and Overview
Real-time video processing involves the editing, analyzing, or encoding/decoding of video streams with little lag time. The goal of real-time processing is to limit the amount of time passed between action and output of the video data. The video can either be live streamed or it can be rendered for quick feedback, depending on the needs of the user.
Why is Real-Time Processing Important?
Real-time video processing is necessary for systems that require feedback without lag. For example video conferencing, surveillance or gaming are especially sensitive to video latency and require high quality and high speed video processing. Without the ability to process video without a time delay, such services will surely show poor video quality, longer processing times and inertia.
Key Components in Real-Time Video Systems
In creating a real-time video processing system, there are usually three major components in constructing video:
- Capture: This involves the use of cameras or other devices to get the required video data.
- Processing: The video that has been captured is then processed through various algorithms for enhancement, object recognition and transformation.
- Output/Display: The enhanced video is then displayed for the users and, if needed, gets saved for further use.
2. The Science of Video: How It Works
Video Compression and Encoding
Video processing involves many stages and one of them includes encoding the video. What arises for videos is that they can take a lot of space, so they have to be made smaller using encoding compression so they can be sent or stored. Compression algorithms make video files smaller while attempting to achieve the best quality possible. Some popular video codecs are H.264, H.265 (HEVC), VP8, and AV1. These video codecs each differ in compression effectiveness and the amount of work that must be done to them.
Video Decoding
On the other side of video processing is decoding. After a video stream has been compressed and sent out, it needs to be expanded (decoded) in order to be played or worked on. Reconstruction of the video data is done using decoding algorithms, which then enable the users to view or manipulate the files.
Frame Rate and Resolution
A video’s fingerprint is described by its frame rate (the number of frames per second) and video resolution (the number of pixels in a single frame). Video resolutions could be 4K, 1080P, 720P, or 480P. The image quality can be boosted with high resolution, but this would take away a lot of computing power and resources as needed. Additionally, the frame rate plays a crucial role ’s resource intensive however it enhances a video’s fluidity (for example 60fps is considerably smoother than 30fps)
3. Key Technologies in Real-Time Video Processing
Real Time Video Processing Hardware
The hardware has to be of top performance otherwise real time video processing becomes difficult. Video processing turns out to be a multiprocessor task enabling efficient RTA operations and parallel video editing, rendering, encoding as multiple tasks need to be done simultaneously which can be achieved through the use of the Graphics Processing Unit (GPU).
For quicker video processing, increasing numbers of specialized hardware components, including ASICs, FPGAs, and DSPs, are being employed to speed up the various tasks.
Software Frameworks and Libraries
When it comes to video editing, a multitude of software libraries and frameworks have been created to aid with the process, including;
- OpenCV: Assists in computer vision application which includes Real time video editing and is famous due to being open source.
- FFmpeg: It is a handy suite for multimedia applications that offer encoding, decoding, transcoding and streaming
- GStreamer: Helps in developing streaming media applications.
These libraries speed up the developer because they come with ready-made functions and algorithms such as video editing, video compression, and video analytics.
Cloud Computing and Edge Network
Real-time video processing is greatly assisted by the cloud and edge networks. By relying on a cloud structure, an enterprise can always scale their video processing capabilities as required, with many video files kept and heavily processed algorithms operated from dedicated servers. Unfortunately, uploading algorithms depends on the video streams bandwidth, which can add latency when transferred over the internet unlike processing in the cloud.
Edge computing is useful in avoiding latency in that it processes the video at the site of origin which lowers the amount of data traffic that the cloud has to deal with. This is important in image processing for applications such as autonomous cars or security where speed and low latency are imperative.
Artificial Intelligence and Machine Learning in Video Processing
AI and machine learning are changing the way real time video is processed. Algorithms fed with a sufficient amount of information can be applied in specific tasks such as:
- Object Detection and Tracking: Analysis of video frames in a video clip to identify and pursue new moving objects is one of the tasks that AI can tackle.
- Face Recognition: It’s possible to develop algorithms that can pick up any single person from a live streamed video and ascertain their identity.
- Video Enhancement: AI technologies can be used for real time video enhancement through super resolution, noise or color corrections among others.
4. Real-Time Video Processing Use Cases
Video Streaming Platforms
Real Time Video Processing is mostly employed in Live Broadcasting and Video on Demand services by streaming platforms such as Netflix, Youtube, Twitch to name a few. Every other person ends up being a user who requires the stream to be first, compressed, encoded, and then transferred to them while making use of an entirely new set of devices that can capture lower to higher quality and formats while also ensuring that there is negligible delay.
Video Surveillance and Security
When it comes to security, real time video processing makes it possible to conduct live surveillance operations, detect any movements and even scan a face. Video processing is used by security cameras with built-in functionalities that allow them to monitor and film scenes and show them to operators with the goal of providing them with information about potential risks such as break-ins.
Augmented Reality (AR) and Virtual Reality (VR)
These technologies can only become better with the integration of video processing which would make it lot more natural. When an AR device is being used, for instance, video taken from a camera can be used to create real-time digital images to be plastered into the real environment – the delay between capturing the image and the processing of the image should be kept at a maximum low. In VR equipment, the video that is being displayed has to be rendered in accordance with how the user is moving their head so that the session continues being smooth and looks realistic.
Healthcare and Medical Imaging
In the medical field, video movies are modified in real-time video movie processing while doing surgical cases which involve minimally invasive techniques. They are able to get real time feedback from specialists using these systems. Moreover, AI-assisted image analysis can help diagnose diseases as it aims to leverage real time diagnostic image signals.
Autonomous Vehicles
Autonomous vehicles also use video processing in order to understand spatial information. The information required to drive the vehicle which are videos from the cameras, lidar and radar video feeds are processed in real time to locate keywords such as other vehicles, pedestrians, road signs and stationary objects making it possible to drive the vehicle without a human.
5. Challenges in Real-Time Video Processing
Despite numerous applications of video image processing, this technology also creates some problems some of which include:
Latency and Bandwidth Issues
Latency is the interval between the frame of video captured and when that frame is displayed or stored. Too much lag can be detrimental to the user experience especially in applications like streaming videos, playing games online or having a one on one video call. There is also the problem of low bandwidth which aggravate the problem of time real transmission of video.
Data Loss and Corruption:
Data loss/loss of integrity can occur due to bandwidth issues during video streaming and this could result in a lack of video quality or a delay in services offered.
Hardware Limitations:
Real time video processing and editing requires powerful hardware, however, it is possible that there are limited resources available for an organization to fully complete these tasks in an optimized manner. In many situations it is not practical to obtain GPUs, TPUs and other hardware due to the high cost that is incurred.
Power Consumption:
So much power is utilized when processing videos through mobile devices or embedded systems that the battery life of the devices being utilized gets drained and this has proved to be the case in portable systems where the processing delay has to be kept to a minimum.