Statistical Background Subtraction for a Mobile Observer

13 years 7 months ago
Statistical Background Subtraction for a Mobile Observer
Statistical background modelling and subtraction has proved to be a popular and effective class of algorithms for segmenting independently moving foreground objects out from a static background, without requiring any a priori information of the properties of foreground objects. This paper presents two contributions on this topic, aimed towards robotics where an active head is mounted on a mobile vehicle. In periods when the vehicle's wheels are not driven, camera translation is virtually zero, and background subtraction techniques are applicable. Parts of this work are also highly relevant to surveillance and video conferencing. The first part of the paper presents an efficient probabilistic framework for when the camera pans and tilts. A unified approach is developed for handling various sources of error, including motion blur, sub-pixel camera motion, mixed pixels at object boundaries, and also uncertainty in background stabilisation caused by noise, unmodelled radial distortio...
Eric Hayman, Jan-Olof Eklundh
Added 15 Oct 2009
Updated 31 Oct 2009
Type Conference
Year 2003
Where ICCV
Authors Eric Hayman, Jan-Olof Eklundh
Comments (1)
IMG_0674-1.jpgDoubts regarding an equation

I am facing difficulty in understanding equation (12) in section 4.1

a) Is 'i' from 1 to H+1 ? If yes,how (H+1)th model fits in the equation?

b) when H=1, does P(A1|Z,M) becomes 1?

Can anyone help me?

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