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What is Computer Vision (CV)?

Computer vision (CV) is a field of artificial intelligence (AI) that enables machines to interpret, process and analyze visual data from the world, such as images, objects and even people. This technology empowers computers to perform tasks that typically require human vision, such as identifying objects, recognizing faces and detecting patterns. By mimicking human sight, computer vision has revolutionized enterprise functions from sales to talent acquisition, making it an essential component of modern enterprise AI solutions.

How does computer vision work?

Computer vision works by leveraging advanced algorithms, deep learning models and large datasets to teach machines how to interpret visual information. Here’s a simplified breakdown of the process: 

Image
acquisition

The process begins by capturing images or video using cameras or sensors.

Image
processing

Raw data is converted into a format suitable for analysis, often through techniques like edge detection or noise reduction.

Feature extraction

Key details such as shapes, colors and textures are identified.

Analysis and interpretation

Key details such as shapes, colors and textures are identified.

Deep learning, particularly convolutional neural networks (CNNs), plays a pivotal role in achieving high accuracy in tasks like object detection and image classification.

Applications of computer vision

Computer vision is transforming industries by core enterprise functions, enabling automationdeeper customer understanding, improveding efficiency and enhanceding user experiences. Here are some of its most impactful applications: 

Sales

AI-powered sales assistants, like Uniphore’s Q for Sales, use computer vision for:

  • Augmenting sellers’ emotional awareness during remote sales engagements (i.e. “reading the room”)
  • Gauging buyer engagement using facial expressions, body language and more

Talent acquisition

In recruiting, AI-powered copilots, like Q for Recruiting, leverage computer vision for:

  • Enhancing recruiters’ ability to read candidates’ non-verbal cues during remote interviews and other interactions
  • Combining visual data with other insights to help organizations make more informed, data-driven hiring decisions

Security and surveillance

Computer vision is a common component of many authentication programs for:

  • Identifying unauthorized access through facial recognition
  • etecting suspicious activities in real time

Benefits of computer vision for enterprises

Computer vision offers numerous advantages for businesses, making it a cornerstone technology for enterprise AI solutions: 

  • Skill augmentation: Computer vision enhances interpersonal skills that are lost or muted during video engagements.
  • Enhanced accuracy: Automated visual systems reduce human error, ensuring precision in critical processes.
  • Improved efficiency: Core business functions, like sales or recruiting, can be performed more effectively and consistently.
  • Data-driven decision making: CV-generated insights can help organizations make better sales, hiring and other business-critical decisions.
  • Richer user experiences: From personalized selling to more positive and productive interviews, CV enriches how businesses engage with others.

Challenges in computer vision

Despite its remarkable potential, computer vision faces several challenges: 

Data
quality

Poor-quality images can affect accuracy.

Bias in
algorithms

Inadequate or unbalanced training data can lead to biased outputs.

High computational requirements

Processing visual data demands significant computational power.

Privacy
concerns

Using cameras and sensors for data collection raises ethical and legal questions.

Addressing these challenges requires robust data strategies, ethical frameworks and cutting-edge technology.

Future trends in computer vision

Pioneering advancements, including those already in use in Uniphore’s Q products, are already shaping the future of computer vision. These include: 

  • Real-time analysis: Enhanced processing speeds are making real-time video analysis a reality.
  • Emotional intelligence: Advanced facial analysis is enabling businesses to understand customer sentiment and emotion with greater accuracy than ever before.
  • Engagement tracking: CV analysis is allowing businesses to monitor and measure engagement levels during key interactions, like sales pitches and interviews.

Learn more

At Uniphore, we are at the forefront of leveraging AI technologies like computer vision to drive innovation and efficiency. Our Q product portfolio, which includes Q for Sales and Q for Recruiting, combines CV with other game-changing AI applications to enhance employee capabilities and optimize core business functions.

To learn more about Uniphore, visit our homepage. For more glossary terms, check out our comprehensive AI glossary.

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