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Hidden Markov Model (HMM)

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Hidden Markov Model (HMM)  VIDEO LINK:  https://youtu.be/YIGCWNG8BIA A Hidden Markov Model (HMM) is a statistical model in which the system has hidden states that cannot be directly observed, but produce observable outputs. It is based on the Markov property, meaning the next state depends only on the current state. Video Chapters: HMM in Artificial Intelligence 00:00 Introduction 00:31 Statistical Model 00:54 HMM Examples 02:30 HMM 03:10 HMM Components 05:23 Viterbi Algorithm 06:23 HMM Applications 06:38 HMM Problems 07:28 HMM in Handwriting Recognition 11:20 Conclusion  HMM COMPONENTS A Hidden Markov Model (HMM) is a statistical model in which the system has hidden states that cannot be directly observed, but produce observable outputs. It is based on the Markov property, meaning the next state depends only on the current state. An HMM consists of states, observations, transition probabilities, emission probabilities, and initial probabilities. It is commonly used in a...
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Viewing Pipeline - 2 Dimensional Viewing in Computer Graphics

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 Viewing Pipeline: Viewing Transformation in several steps:

1. Modeling Coordinates

2. World Coordinate System

3. Clipping Window

4. Normalize - Normalized Coordinates 

5. Device Coordinate 

6. ViewPort

7. Clipping

First, we construct the scene in the world coordinates using the output primitives. Next, obtain a particular orientation for the window, we can set up a 2D viewing coordinate plane and define windows in the viewing coordinate system.

The viewing coordinate reference frame is used to provide a method for setting up arbitrary orientations for a rectangular window. 

Once the viewing reference frame is established. we can transform description in the world coordinate to viewing coordinates.

After that define a viewport in normalized coordinates ( in the range from 0 to 1).

2D Viewing Pipeline can be achieved by the following steps: 

1. Construct world coordinate scene using modeling coordinate transformation. 

2. convert world coordinates to viewing coordinates.

3. Transform viewing coordinate to normalized coordinates (i.e., Between 0 and 1, or between -1 and 1)

4. MAP normalized coordinates to device coordinates. 

WINDOW TO VIEWPORT COORDINATE TRANSFORMATION

This is also known as window viewport transform or windowing transformation.

MAPPING of a part of a world coordinate scene to device coordinates is referenced as viewing transformation.

VIEWPORT COORDINATE TRANSFORMATION - 3 MAIN STEPS

1. Object with its window is translated until the lower-left corner of the window is at the origin.

ORIGINAL 
AFTER Translation 

2. Object and window are now scaled until the window has the dimension the same as the viewport. We are converting the object into the image and window in the viewport. 

AFTER Scaling

3. Another Translation to move the viewport to its correct position on the screen.




Viewing Transformation performed in 3 Steps: Translation, Scaling and again Translation. 


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