Video content is exploding across every industry. Cisco predicts video will make up 82% of all internet traffic by 2022. With this video deluge, AI video analytics tools are becoming indispensable for extracting value from all this rich data. These intelligent platforms automate the analysis process to provide invaluable and actionable insights impossible for humans to gather on their own.
In this post, we‘ll highlight 5 top AI video analytics platforms revolutionizing how organizations gather intelligence from video, save on manual analysis costs, and drive better business decisions.
Why AI Video Analytics Platforms Are Taking Off
As video content and camera hardware continue improving rapidly, video data is getting more complex. Static cameras are being replaced with 4K cameras, 360 capture, body cams and drones. The variety and volume have gone through the roof.
Manually analyzing even a fraction of accumulated video is no longer realistic for most companies. And missing critical events hidden inside all this video essentially means lost insights and opportunities.
Powerful AI video analytics platforms solve this by automating the video analysis process with:
Advanced Computer Vision – Platforms use machine learning models trained on millions of videos to achieve human-like understanding of video footage. This allows them to pinpoint people, objects, scenes, text and more with high accuracy.
Video Intelligence APIs – Developers can tap into rich APIs to build custom video analysis functionality into their own industry applications and workflows based on unique needs.
Flexibility & Scalability – Leading platforms leverage cloud-based processing for unlimited scale. And their machine learning pipelines continually improve through more data, allowing video analytics to expand across any number of use cases.
With these AI-driven capabilities, video analytics platforms are delivering tremendous value across sectors like security, marketing, retail, manufacturing, government and healthcare.
5 Top AI Video Analytics Platforms to Know
1. Amazon Rekognition
As an industry leader in the cloud services space, Amazon offers extremely powerful and scalable video analysis via Amazon Rekognition.
Key capabilities include:
- Facial analysis – Detect, analyze and compare faces for a wide variety of applications from identity verification to people counting.
- Real-time face search – Search faces detected in streaming video against watchlists to identify persons of interest.
- Object and scene detection – Pinpoints objects, scenes and activities inside video to understand video context and build metadata.
- Text analysis – Detect and analyze text within images/video for use cases like license plate recognition and document parsing.
With Rekognition, you get the same proven infrastructure that powers Amazon.com‘s product recommendations and Prime Video search.
2. IBM Watson
IBM Watson delivers an enterprise-grade video analytics and intelligence platform leveraging AI and machine learning.
Capabilities span:
- Global image tagging, text recognition and face detection
- Custom visual recognition models
- Annotate videos with scene-level metadata
- Search videos 700x faster using auto-generated transcripts
- Analyze audience reactions via emotion analysis
Watson makes video easily searchable while extracting meaning that connects it to other data sources.
3. Microsoft Azure Video Analyzer
Part of Microsoft‘s industry-leading cloud platform, Azure Video Analyzer enables intelligent video analytics pipelines.
Built-in features include:
- Motion detection that triggers alerts and other actions
- Facial recognition to identify people of interest
- Anomaly detection such as loitering and crowd density alerts
- Analytics dashboards and reporting options
As expected with Azure, developers have the full set of AI tools to build custom video analytics scenarios.
4. BriefCam
BriefCam offers an award-winning video content analytics platform tuned for rapid video review and search.
Unique aspects include:
- Quick video synopsis and summarization
- Find similar video content for faster investigations
- Pixelated masking options to protect identities
- Multimedia analytics structured into a timeline view
BriefCam accelerates post-event investigations that would normally require hours of manual footage review by investigators.
5. Gorilla Technology
Gorilla Technology develops video IoT analytics solutions focused on security and manufacturing use cases.
Their AI engine excels at functions like:
- Crowd monitoring
- Intrusion detection
- Dangerous behavior ID
- Traffic incident alerts
- Analytics for assembly lines and warehouses
Gorilla combines computer vision and edge computing to deliver actionable intelligence even under tough conditions like low/variable lighting, occlusions and differing angles.
Real-World AI Video Analytics Use Cases
Let‘s look at some examples that showcase the versatility and business value unlocked by AI video analytics:
Retail – Store owners add video analytics to cameras for measuring foot traffic, dwell time, customer engagement and operational analytics like queue lengths, lost sales opportunities and ideal product placement.
Transportation – Video streams from traffic or public transit cameras feed into models that analyze vehicle/passenger flow, dangerous driving, accident detection and more.
Security – Banks, casinos, airports and industrial sites use video analytics for perimeter protection, identifying persons of interest, suspicious behavior detection, and mitigating theft and vandalism.
Manufacturing – Defect spotting on assembly lines, inventory tracking in warehouses, worker safety and optimizing operations are key manufacturing applications.
Media & Entertainment – Automatically tag videos, moderate content, recognize objects/logos, compile clips and deliver personalized viewing experiences.
Healthcare – Patient flow monitoring, fall detection for seniors, sentiment analysis, operating room surveillance and medical imaging analytics.
And many more applications are emerging across other verticals like government, education and hospitality.
The Future of AI Video Analytics
AI video analytics platforms have already made great strides. But we are still just scratching the surface of possibilities as the underlying machine learning models continue evolving.
According to MarketsandMarkets, the video analytics market size will reach $13.34 billion by 2027, up from $4.58 billion in 2020. Increased enterprise adoption across untapped sectors will drive rapid growth along with technology advancements.
In coming years, expect platforms to move from mainly descriptive analytics to delivering predictive, prescriptive and preemptive video intelligence. This shift will bring exciting new applications.
For instance, being able to predict where crimes are likely to occur so law enforcement can allocate resources accordingly. Or retail operations receiving guidance on optimal store layouts and inventory based on models interpreting a diverse dataset including sales numbers, foot traffic, dwell times and video-derived customer behavior analytics.
The big data from video offers tremendous potential when paired with modern AI. Video analytics platforms make this combination available out-of-the-box so businesses can fast-track data science initiatives and enter new innovation frontiers in their market landscapes.
Get Started With Smarter Video Analytics
As this post outlines, AI video analytics platforms bring game-changing capabilities that transform security operations, business efficiency, decision-making and customer experiences spanning every industry.
Key next steps for implementing video analytics include:
-
Documenting critical processes/areas to focus analytics on based on current pain points and future priorities
-
Assessing necessary camera and edge hardware upgrades
-
Comparing leading video analytics platforms that align with use case requirements
-
Testing tools on high-impact pilot use cases before expanding analytics capabilities at scale
Now is the time to formulate video analytics adoption roadmaps to drive savings, uncover hidden insights in video data, and enable data-led growth strategies. Reach out if you need any assistance jumpstarting video analytics initiatives.
