How to detect occlusion in moving camera environment?

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Volker Lohweg

Hi,

maybe this first input helps for the start: https://www.researchgate.net/publication/266652723_Occlusion_Detection_for_Textured_2D_Objects_on_a_Heap

Conference Paper Occlusion Detection for Textured 2D Objects on a Heap

John Sosa

Hi Sandeep,

I'd be happy to see if our new software MIPAR (http://MIPAR.us) could work well for you -- I think it could! I'd love to take a look at some sample frames you have to come up with the detection algorithm. Any chance you could attach a few or message them over?

Cheers,

John

Vikas Ramachandra

Usually, front-back and back-front flow vectors and computed and regions where they dont match are flagged as occlusions (a simple method)

Saber Shakeri

you must use Motion Detection if you want do this work in Real-Time

Sandeep Singh Sengar

Thanks for your suggestions. I just want to use it as a pre-processing task to further process by some other methods. So can I use the intensity difference between two successive frames (corresponding samples from two successive frames) and apply thresholding to check the occlusion (but it is in moving environment, so I have a doubt). I just want a simple approach.

Could you post a couple of frames?

Sorry, I don't want to use software.

Hadi sadoghi yazdi

SIFT features is suitable.

also used CNN for tracking.

Touseef Ali

Kalman Filter should work for you

Dear Hadi and Touseef,

I am using Haar like features with multiple instance learning. For that I am find the features in the subregions of samples as a pre-processing task. I will not extract the haar like features from the occluded subregion. For that I need to find the occluded subregions.

One paper is attached here for the same concept, but in this paper details about occlusion handling is not provided.

Shafagat Mahmudova

Dear Sandeep Singh Sengar,

Look the link, may be useful.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4377503/

http://www-users.cs.umn.edu/~jackson/Papers/Occlusions/paper.pdf

Regards, Shafagat

Sathish Dhandapani

Pdf will help you

André Stanzani Franca

Dear Sandeep,

You are using Haar like features, right? So it´s easy to calculate moving object's volume. If this volume suddenly decreases, the moving object is behind a wall (the occlusion). If the volume increases, the moving object left behind the wall. May it works.

best regards