Visual Intelligence Overview
Visual content has grown at an unprecedented rate over the last decade.
Every minute, 404,444 hours of content are streamed by Netflix users, 500 hours of videos are uploaded to YouTube, 347,222 user stories are posted on Instagram, and 147,000 photos are uploaded on Facebook.1 All of this is just consumer-generated content. It does not include visual content generated by machines – drones, satellites, healthcare imaging systems, surveillance cameras, etc.
The global image recognition market size is expected to reach $109.4 billion by 2027 and grow at a CAGR of 18.8% from 2020 to 2027. The global video analytics market is expected to reach $4.1 billion million by 2025, registering a CAGR of 24.5% from 2020 to 2025.3
The market is booming, and businesses can no longer ignore this opportunity. However, some of the common challenges that businesses face are:
- Low-quality images and videos, including blurriness, skewing, and lack of contras
- The problem of fake and deepfake pictures and videos
- Storage and processing challenges
- Lack of accurate contextualization of machine-generated output
- Unavailability of training data sets
Why Straive’s Visual Intelligence Solutions?
We leverage computer vision technology combined with our unstructured data solutions experience to transform the way visual content is processed and consumed. Straive’s vision-led image and video processing solutions have enabled clients to transform their business processes. Our solutions offer them the capability to extract information, recognize objects and entities, classify images, develop patterns, identify gestures, and faces/persons on an industrial scale through the Straive Data Platform (SDP).
Key Benefits
Acquisition: Able to acquire high-quality datasets from diverse sources through web scraping from the public domain, connector to clients’ databases, SFTPs, or external API calls
Noise Removal and Enhancement: Removes noise and aberrations from images by leveraging statistical models to detect and compensate for blur, to improve focus, saturation, contrast, etc., which make standard AI models less effective
Transformation: Standardizes formats and sizes of the images and videos, including compression and decompression
Data Labelling: Able to create high-velocity training data sets by leveraging the annotation engine to enable training and quick deployment of models
Object Recognition: Identifies specific entities or objects and patterns in the images and videos using AI models to convert unstructured visual content into structured datasets
The collection of source data can be automated and includes real-time monitoring of websites for any changes or new information. It extracts relevant content, de-duplicates, structures, and normalizes the content as illustrated in the sample process for extracting executive contacts from public sources.
Where Can You Use Straive’s Vision Intelligence Solutions?
Advertising Intelligence
Identifies logos, products, and brands from advertisements across TV, digital, and print media
Insurance Damage Estimation
Estimates damages to rooftops, vehicles, warehouses, and buildings using drone images
Retail Markets
Develops an accurate view of SKUs on store shelves and identifies product placement and stockouts
Consumer Sentiment
Identifies actual consumer sentiment through facial and body language cues from consumer videos
Telematics and Urban Planning
Identifies signages, speed limits, road markings, streetlights, and road conditions using LIDAR image
Medical Image Analysis:
Detects diseases and anomalies such as tumors, cancerous cells in X-rays, CT scans, etc.
Insights
We want tohear from you
Our solutioning team is eager to know about your challenge and how we can help.