julioexam

• refers to the process of converting continuous visual

  information computers into a discrete form that can manipulate.

  It involves capturing and representing video and at specific points in time and space.

  Sampling
• Sampling occurs in two main domains

  Spatial Domain

  Temporal Domain
• refers to the process of dividing the visual scene, such as an image or video into a grid of points called frame, discrete pixels.

  Spatial Sampling
• The visual scene is divided into a grid of pixels, with each pixel

  assigned a specific location and color value.

  Pixel Grid
• refers to the number of pixels it contains. Higher resolutions result in

  sharper and more detailed images.

  Spatial-Resolution
• each pixel determines the level of detail that can be captured in

  the image. Smaller pixels allow for finer details to be represented

  pixel size
• refers to how densely the pixels are packed in the image. Higher

  sampling frequencies result in higher resolutions and more detailed

  images.

  Sample Frequency
• It is a phenomenon that occurs when the sampling rate is insufficient

  to accurately represent the original continuous signal. It leads to

  inaccuracies and distortions in the reconstructed signal.

  Aliasing
• in video processing involves capturing a series of images (frames) over time to represent motion. It determines how frequently frames are captured and stored, which directly affects the smoothness and fidelity

  of motion in the video.

  Temporal Sampling
• It determines how many frames are captured per second. Higher

  frame rates result in smoother motion but require more data storage

  and processing power.

  Frame rates
• Each frame captures a snapshot of the scene at a specific point in

  time. When played back sequentially, these frames create the illusion

  of motion.

  Motion Representation
• refers to the level of detail in the temporal

  domain. Higher frame rates provide better temporal resolution,

  allowing for smoother and more natural-looking motion.

  Temporal Resolution
• Insufficient temporal sampling can lead to temporal aliasing, where

  fast- moving objects appear blurred or distorted. To avoid temporal

  aliasing, it's important to use a frame rate that is high enough to

  accurately represent the motion in the scene.

  Temporal Aliasing
• states that in order to accurately sample

  a signal, the sampling frequency must be at least twice the

  highest frequency component of the signal. This prevents

  aliasing, where high-frequency signals are misrepresented at lower

  frequencies. It is crucial in digital signal processing and

  telecommunications.

  Nyquist Theorem
• The two main creators of Nyquist Theorem

  Harry Nyquist Claude Shannon,
• Scanning of analog signals choosing atleast twice the highest frequency present in the signal and ensures there's enough samples

  to capture the variation of signals

  Nyquist Criterion
• is a fundamental process in various fields like video compression, computer vision, and robotic navigation. It involves analyzing consecutive frames of video to determine the motion of objects within the frames.

  Motion Estimation
• refers to the visual depiction or description of movement in a graphical or symbolic form.

  Motion Representation
• refers to the methods and techniques used to describe and analyze the movement of objects or regions within a sequence of frames.

  Motion Representation
• ●technique used in video compression to reduce redundancy by comparing blocks of pixels between frames.

  Block-based motion estimation
• ●technique used in computer vision to analyze and track large-scale motion in video sequences.

  global motion estimation
• are technologies that enable the real-time monitoring and tracing of objects or subjects within a specified area.

  Object tracking systems,Virtual and Augmented Reality, Gesture Recognition, Medical Imaging and Analysis, Robotics and Autonomous Vehicles
• is a fundamental concept in computer vision that describes the apparent motion of objects in an image or video sequence.

  Optical Flow
• is a widely used technique for optical flow estimation developed by Bruce D. Lucas and Takeo Kanade.


  The Lucas-Kanade method
• It assumes that the motion between frames is locally constant within a small neighborhood of pixels.

  Lucas-Kanade method
• It models optical flow as a smooth vector field that satisfies the brightness constancy constraint, which states that the intensity of a pixel remains constant over time.


  Horn-Schunck method
• in video processing refers to the process of generating intermediate frames between existing frames in a video sequence

  Interpolation
• Determine the original frames in the video sequence between which interpolation is required. These Key frames serve as the reference points for generating intermediate frames

  Identify Key frames
• • Select an Interpolation method appropriate for the specific application and desired outcome.

  Interpolation Method
• Apply the chosen interpolation method to estimate the values of pixels or image features in the intermediate frames. This involves interpolating the pixel values based on the known values of neighboring pixels in the original frames.


  Generate Intermediate frames
• • Finishing with combining all of the generated frames to create an interpolated result of the raw video


  merging of frames