I'm using a bayesian framework to estimate the pose of a moving vehicle with a single camera. The state vector of the vehicle is X = [ x y θ ] where x and y are the coordinates in the plan and θ is the heading angle. The state vector X is constatntly updated in the prediction step.In the correction step, an image retrieval algorithm compares the current image to a database of images by a measure based on pixel by pixel differences. Then, it returns the best match which is an image of index j ∈ N together with its pose, the measurement z = [ x m y m θ m ] Let's say my current image is actually the image of index j=1000 but the algorithm returns j=1005, how to evaluate the uncertainty? How to calculate the covariance matrix of this measurement?

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I&#039;m using a bayesian framework to estimate the pose of a moving vehicle with a single camera. The state vector of the vehicle is  X  =      [                            x                                      y                                      θ                      ]  where x and y are the coordinates in the plan and   θ is the heading angle. The state vector X is constatntly updated in the prediction step.In the correction step, an image retrieval algorithm compares the current image to a database of images by a measure based on pixel by pixel differences. Then, it returns the best match which is an image of index   j  ∈  N together with its pose, the measurement   z  =      [                                        x                          m                                                                        y                          m                                                                        θ                          m                                            ]  Let&#039;s say my current image is actually the image of index j=1000 but the algorithm returns j=1005, how to evaluate the uncertainty? How to calculate the covariance matrix of this measurement?

Duncan Cox · Accepted Answer

I would post this as a comment, but I don&#039;t have enough rep. You can have a look at Confusion Matrix. Not sure if this is what you&#039;re looking for though.

I'm using a bayesian framework to estimate the pose of a moving vehicle with a single camera. The st

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