By Dr. Zhengyou Zhang, Dr. Olivier Faugeras (auth.)
he challenge of studying sequences of pictures to extract third-dimensional T movement and constitution has been on the middle of the learn in laptop vi sion for a few years. you will need to seeing that its good fortune or failure will ensure even if imaginative and prescient can be utilized as a sensory approach in reactive structures. The huge examine curiosity during this box has been stimulated at the very least through the subsequent issues: 1. The redundancy of data contained in time-varying photos can over come numerous problems encountered in examining a unmarried photo. 2. there are various vital purposes together with computerized car driv ing, site visitors regulate, aerial surveillance, clinical inspection and international version development. in spite of the fact that, there are lots of new difficulties which will be solved: easy methods to effi ciently method the ample info contained in time-varying photos, easy methods to version the swap among pictures, easy methods to version the uncertainty inherently linked to the imaging process and the way to unravel inverse difficulties that are in general ill-posed. there are naturally many probabilities for attacking those difficulties and plenty of extra stay to be explored. We talk about some of them during this ebook in keeping with paintings performed over the past 5 years within the computing device imaginative and prescient and Robotics team at INRIA (Institut nationwide de Recherche en Informatique et en Automatique).
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Additional resources for 3D Dynamic Scene Analysis: A Stereo Based Approach
Its covariance matrix is where Ai is the covariance matrix of the corresponding endpoint in camera i. Here we assume there is no correlation between Xabpq and 2D endpoints. Strictly speaking, there does exist a little correlation because Xabpq have been computed from 2D endpoints. 7, 8,23]. 5 Summary In this chapter, we have first discussed why line segments are chosen as our basic primitives for motion analysis. Using line segments allows us to obtain a relatively compact and structured representation of the environment.
23J. 4). 5) See the appendix to this monograph for the definition of the vector differentiation. 8) where Vij is the jth element of Vi. As A, b ab and b pq are affine functions of the Vii'S (i,j = 1,2,3), those partial derivatives are very simple to compute. In fact, what we have estimated at this stage is the infinite line S supporting the segment we want. To recover the 3D segment, several approaches can be considered. We describe one of them. We consider only one endpoint of the segment. The same computation is applied for the other.
17) where MI and M2 are two points on the line. A minimal representation of a straight line is four-dimensional. 14,15]' a representation called abpq was adopted. Under this representation, a line is represented as the intersection of two planes: x = az y = bz + q . 18) This is a quasi-minimal representation. The four parameters are [a, b, p, q]T. The line goes through the point [p, q, O]T and is parallel to the vector [a, b, If. 18) cannot represent lines parallel to the xy-plane. To fully define a 3D line, two other representations are required.