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I'm developing an image processing project and I come across the word occlusion in many scientific papers, what do occlusions mean in the context of image processing? The dictionary is only giving a general definition. Can anyone describe them using an image as a context?
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Put simply, occlusion in an image occurs when an object hides a part of another object. The areas that are occluded depend on the position of the camera relative to the scene.
Definition. Occlusion detection refers to the set of techniques employed to detect which areas of the images are occlusion boundaries or areas that appear occluded in views of the scene.
Occlusion means that there is something you want to see, but can't due to some property of your sensor setup, or some event. Exactly how it manifests itself or how you deal with the problem will vary due to the problem at hand.
Occlusions are pixels in which the object of interest is hidden because it is obstructed by an object nearer to the observer. These last two classes are distinct because occlusions cover the target and may split the figure information into two or more nonadjacent regions.
Occlusion means that there is something you want to see, but can't due to some property of your sensor setup, or some event. Exactly how it manifests itself or how you deal with the problem will vary due to the problem at hand.
Some examples:
If you are developing a system which tracks objects (people, cars, ...) then occlusion occurs if an object you are tracking is hidden (occluded) by another object. Like two persons walking past each other, or a car that drives under a bridge. The problem in this case is what you do when an object disappears and reappears again.
If you are using a range camera, then occlusion is areas where you do not have any information. Some laser range cameras works by transmitting a laser beam onto the surface you are examining and then having a camera setup which identifies the point of impact of that laser in the resulting image. That gives the 3D-coordinates of that point. However, since the camera and laser is not necessarily aligned there can be points on the examined surface which the camera can see but the laser can not hit (occlusion). The problem here is more a matter of sensor setup.
The same can occur in stereo imaging if there are parts of the scene which are only seen by one of the two cameras. No range data can obviously be collected from these points.
There are probably more examples.
If you specify your problem, then maybe we can define what occlusion is in that case, and what problems it entails
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The problem of occlusion is one of the main reasons why computer vision is hard in general. Specifically, this is much more problematic in Object Tracking. See the below figures:
Notice, how the lady's face is not completely visible in frames 0519 & 0835 as opposed to the face in frame 0005.
And here's one more picture where the face of the man is partially hidden in all three frames.
Notice in the below image how the tracking of the couple in red & green bounding box is lost in the middle frame due to occlusion (i.e. partially hidden by another person in front of them) but correctly tracked in the last frame when they become (almost) completely visible.
Picture courtesy: Stanford, USC
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