Computer vision is the goal of writing programs that can interpret images, such as video sequences or medical scans. It involves acquiring images, preprocessing them, extracting features, detecting/segmenting objects, and recognizing/interpreting the images. Computer vision draws from fields like calculus, linear algebra, and statistics. It has applications in areas like robotics, navigation, inspection, and medical imaging. While computer vision has improved, it still lacks the subtlety and versatility of human vision.

1. Computer Vision
Presented by:- Kartik N. Kalpande

2. • Image Understanding
• Appeared in 1960s
• A sensor modality for robotics
• Computer emulation of human vision
• Inverse of Computer Graphics
Computer
vision
World
model
Computer
graphics
World
model

3.  Goal of computer vision is to write computer programs that
can interpret images.
 The image data can take many forms, such as a video
sequence, depth images, views from multiple cameras, or
multi-dimensional data from a medical scanner

4. What we see What a computer sees

5.  It is many-to-one mapping.
 It is computationally intensive.
 We do not understand the recognition problem.

7.  Image acquisition
 Pre-processing
 Feature extraction
 Detection/segmentation
 Recognition an interpretation

8.  Calculus
 Linear Algebra
 Probabilities and Statistics
 Signal processing
 Projective geometry
 Computational geometry
 OptimizationTheory
 ControlTheory

9.  Controlling processes
 Navigation
 Detecting events
 Organizing information
 Modeling objects or environments
 Interaction
 Automatic inspection

10. Identifying characters in images of printed or handwritten
text, usually with a view to encoding the text in a format
more amenable to editing or indexing
(eg. ASCII)

11. Identifying or verifying a person from a digital
image or a video frame from a video source.

12. Computing a 3D model of the
scene.

16. INDUSTRIAL ROBOTS MOBILE ROBOTS

17.  3D imaging
(MRI, CT)
 Image guided surgery

18.  Simpler and faster processes – fast computers replace
lengthy visual checks
 Reliability – cameras and computers, as opposed to a
human eye, never get tired. The human factor is
eliminated.
 Accuracy – your final products will be, thanks to
computer vision, flawless
 A wide range of use – ranging from banks to medical
care
 Cost reduction – you save time on people and devices,
faulty products are eliminated

19.  The field of computer vision has vastly
improved since it began in the 1960s.
Computers can now quickly and accurately
recognize thousands of faces, as well as a
growing number of other objects. Although
computer vision currently lacks the subtlety,
versatility, and general capabilities of human
vision, the gap is steadily closing.

20.  https//www.google.com
 https://wikipedia.org/wiki/computer_vision

21. Machines can’t replicate human image recognition.