JNTU
JNTU B.Tech III COMPUTER VISION AND ROBOTICS Previous Question Paper (January/February - 2023 - R18)
Note: i) Question paper consists of Part A, Part B. ii) Part A is compulsory, which carries 25 marks. In Part A, Answer all questions. iii) In Part B, Answer any one question from each unit. Each question carries 10 marks and may have a, b as sub questions.
Part A
Write the short note on CAMERAS.
Answer
Cameras are imaging devices used in computer vision to capture 2D projections of 3D scenes. They function by focusing light through a lens onto a sensor (CCD or CMOS), which converts photons into electrical signals to form a digital image, typically modeled using the pinhole camera geometry.
What is Radiometry?
Answer
Radiometry is the field of physics concerned with the measurement of electromagnetic radiation, including visible light. In computer vision, it focuses on quantifying the flow of light energy from sources, its interaction with surfaces (reflection, absorption), and the intensity reaching the camera sensor, which is essential for understanding image brightness and shading.
What is Texture?
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How do you extract Shape from Texture?
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What do you mean by segmentation?
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What is Stereopsis?
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What is a linear dynamic model?
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Discuss Probabilistic Methods for segmentation.
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Write the Least-Squares Parameter Estimation.
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Comment on Analytical Photogrammetry.
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Part B
Illustrate the Pinhole Cameras with example.
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Identify the Important Special Cases in Measuring Light by taking a use case of your choice.
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Illustrate the Photometric Stereo application.
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Use the Global Shading Models for Interreflections.
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Inspect the process of Estimating Derivatives with Noise.
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Examine the Sampling and Aliasing methods.
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How do you Represent the Texture. Give a example.
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Examine the Spatial Frequency and Fourier Transforms in applying the linear filters.
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Illustrate the Binocular Fusion in Stereopsis.
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Explain segmentation by graph theoretic clustering.
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Illustrate the process of Reconstruction Using More Cameras.
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Make use of Clustering Pixels for Image Segmentation.
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Examine the following Segmentation by Fitting a Model
Fitting Lines
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Fitting Curves.
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Explain the Linear Dynamic Models for tracking.
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How do you handle the Missing Data Problems in probabilistic methods?
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Illustrate the use case of Registration in Medical Imaging Systems.
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Identify the Camera Parameters and the make use of Perspective Projection.
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Identify a method for Obtaining the Hypotheses Using Invariants.
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Make use of Affine Cameras and Affine Projection Equations for geometric camera models.
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