Help in Explaining POSIT algorithm (3D maths)

  • Thread starter Anhar Miah
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In summary, the conversation is about a person seeking help with a project involving using a webcam to track IR LEDs using the POSIT algorithm. They have provided a link to a paper explaining the algorithm and have requested for a simple numerical example to understand it better. They also mention a possible translation of the code to VB6, but it is not a priority. The person has also asked for help in understanding the math behind the algorithm and has provided links to the paper and code in C and Matlab. They mention their familiarity with linear algebra but express some difficulty in understanding it. They also mention being hopeful for help from the community.
  • #1
Anhar Miah
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Hello Everyone,

This is my fisrt post! I have been suggested that this forum's members may be able to help me, this thread was orginially posted in another forum, they have re-directed me towards this community! :

{original post}

Hi guys,

I've been doing some background hobby project based on using a webcam to detect 4 IR LEDs their position is then tracked, using the POSIT algorithm it is possible to calculate the exact location and pose (translation and orientation) of the LEDs.

Anway here is the paper :

http://www.cfar.umd.edu/~daniel/dani...ose25Lines.pdf

it is Daniels DeMenthons classical "POSIT in 25 lines of code"

The maths is a bit too heavy for me, he inlcudes some codes, I was trying to convert this into VB, but that is only half the story,

what I would really like is a detailed numerical example, that I can actually see how it works (the algorithm) because I've tried to understand the mathemtical explantions in the paper but just got confused !

Summay:
(1) A simple numerical example that explains the algorithm
(2) Possibly a VB6 translation (not really that important)

Thanks in advanced!

thanks guys!

Also:

that paper has mathematica code included, I'm wondering if anyone can "reverse" engineer the code to understand it?

Looking forward to replies

Anhar Hussain Miah
 
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  • #2
Bump! anyone?



(why does this thread not appear directly, can only view it under my account?)

EDIT:

its now fine, thread appears correctly.
 
  • #3
Link to pdf is 404
 
  • #4
Last edited:
  • #5
How much linear algebra do you know?
 
  • #6
In theory I should know it well, in practice I haven't touched it in a couple of years! I'll try my best to follow along, if I get stuck I'll point out the bits I don't understand.

Anhar,

ps. going to sleep now, its 4 am in the uk!
 
  • #7


ok, anything? anyone? I've seen people here solving harder maths problems than this, I was fairly hopeful that this board would be able to help, can someone please try.

Thanks guys,
 

1. What is the POSIT algorithm?

The POSIT algorithm, also known as the "Pose from Orthography and Scaling with Iterations" algorithm, is a mathematical method used to estimate the position and orientation of an object in 3D space.

2. How does the POSIT algorithm work?

The POSIT algorithm uses a set of 2D points, known as the projection or image points, and a corresponding set of 3D points, known as the model points, to calculate the object's position and orientation. It iteratively minimizes the error between the projection points and the transformed model points using a least squares approach.

3. What is the purpose of the POSIT algorithm?

The POSIT algorithm is commonly used in computer vision and robotics applications to determine the location and orientation of an object in 3D space. It is often used in conjunction with other algorithms to track and recognize objects in real-time.

4. What are the benefits of using the POSIT algorithm?

The POSIT algorithm is computationally efficient and can provide accurate results even with noisy or incomplete data. It also does not require prior knowledge of the object's shape or size, making it a versatile and flexible option for 3D pose estimation.

5. Are there any limitations to the POSIT algorithm?

The POSIT algorithm may struggle with certain types of objects, such as thin or elongated objects, that do not have distinct 3D features. It also relies on accurate 2D-3D correspondences and may be sensitive to errors in the input data. Additionally, it may not work well in situations where the object's pose changes significantly between frames.

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