swetha(w)-av-presentation-How Computer Vision Has Changed Daily Life.pdf.pdf

Computer Vision is a field of artificial intelligence (AI) that enables computers and systems to derive meaningful information from digital images, videos, and other visual inputs. Based on this data, computers can take specific actions or make decisions.

1. How Computer Vision
Has Changed Daily Life

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Introduction to Computer
Vision Smartphones and
Photography Healthcare
Advancements Security and
Surveillance Autonomous
Vehicles Retail and Shopping
Entertainment and Media
Agriculture and Farming
Challenges and Future
Directions Conclusion
Agenda

3. Introduction to Computer Vision
What is Computer Vision?
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Computer Vision is a field of Artificial Intelligence (AI) that
enables computers to interpret and make decisions based on visual
data from the world.
It involves the development of algorithms and models that allow
machines to process, analyze, and understand images and videos.
Applications include object recognition, facial recognition, image
restoration, and scene reconstruction, among many others.

4. Smartphones and Photography
Computer vision algorithms
enable features like portrait mode,
scene recognition, and real-time
filters, improving photo quality.
AR applications, powered by
computer vision, allow users to
overlay digital objects onto real-world
scenes through their smartphone
cameras.
Augmented Reality
Enhanced Camera
Capabilities

5. Healthcare Advancements
Medical Imaging
Computer vision enhances MRI, CT, and X-ray imaging for
better diagnosis and treatment plans.
Robotic surgery systems use computer vision for precision
and improved patient outcomes.
Surgical Assistance
AI algorithms help detect diseases like cancer early
through pattern recognition in images.
Disease Detection

6. Security and Surveillance
Enhanced Monitoring
Computer vision enables real-time analysis of
video feeds for threat detection and anomaly
identification.
Facial Recognition
Advanced algorithms in computer vision allow
for identifying individuals in real-time, improving
security measures.

7. Autonomous Vehicles
Computer vision enables
vehicles to detect and classify
objects like pedestrians, cyclists,
and other cars.
Vision systems help in
identifying road lanes,
ensuring the vehicle stays
within its lane.
Computer vision allows vehicles
to recognize and interpret
traffic
signs for safe navigation.
Object Detection Lane Keeping Traffic Sign Recognition

8. Retail and Shopping
Streamlining the shopping
experience with computer vision for
faster, cashier-less transactions.
Enhancing accuracy in stock
management and reducing human error
with real-time computer vision systems.
Automated Checkouts
Inventory Management

9. Entertainment and Media
Computer vision
enhances graphics realism
through texture mapping,
motion capture, and
facial recognition.
Used in CGI to create
realistic environments,
characters, and scenes that
blend with live-action
footage.
Algorithms analyze viewing
patterns to suggest
personalized content,
enhancing user experience.
Video Game Graphics Movie Special Effects Content Recommendation

10. Agriculture and Farming
Crop Monitoring
Utilizing drones and satellites with computer
vision to analyze crop health, detect diseases, and
optimize irrigation.
Automated Harvesting
Employing robots equipped with computer vision
to identify ripe produce and efficiently harvest
crops.

11. High computational requirements pose a significant challenge, necessitating powerful
hardware and energy-efficient algorithms.
Data privacy concerns arise due to the vast amounts of visual data collected and analyzed,
requiring robust security measures.
The need for large, annotated datasets for training models limits the scalability and
application in diverse fields.
Future advancements may include the development of more generalized AI models capable
of learning from fewer examples.
Integration of computer vision with other AI technologies like natural language processing
could lead to more holistic and advanced applications.
Challenges and Future Directions
Current Challenges and
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Future Potential
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12. Conclusion
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Computer vision has revolutionized smartphone
photography, enabling features like facial recognition and
enhanced image quality.
In healthcare, computer vision aids in accurate diagnostics and
advanced medical imaging, improving patient outcomes.
Security systems leverage computer vision for real-time
surveillance and threat detection, enhancing public
safety.
Autonomous vehicles rely on computer vision for navigation and
obstacle detection, paving the way for safer transportation.
In retail, computer vision streamlines inventory management and
enables automated checkouts, enhancing the shopping experience.
Key Takeaways