A new object motion estimation technique for video images, based on a genetic algorithm

Dixon, Erica; Markhauser, C.P.; Rao, K. R.

doi:10.1109/30.628754

Cited by 7 publications

(1 citation statement)

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“…In the field of machine vision, coevolution has also been applied successfully. The work of [53] used coevolving populations to estimate motion and layer information of video objects. populations encoded the motion transform parame-ters of each object and another population encoded the layering of the objects.…”

Section: Previous Coevolutionary Paradigmsmentioning

confidence: 99%

A collective-based adaptive symbiotic model for surface reconstruction in area-based stereo

Goulermas¹,

Liatsis

2003

IEEE Trans. Evol. Computat.

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This paper proposes a novel optimization algorithm for image-space matching and three-dimensional space analysis, using an adapted scheme of evolutionary computation that employs the concept of symbiosis in a collective of homogeneous populations. It is applied to the automatic generation of disparity surfaces used for depth estimation in stereo vision. The global task of approximating the complete disparity surface is decomposed to a large number of smaller local problems, each solvable by a smaller processing unit. Coevolution is sustained in such a way as to counteract the arbitrary decomposition of the original super-problem, so that the local evolutions of all the subproblems become interlocked. This, in the long run, provides a consistent global solution, and it does so via an asynchronous and massively parallel architecture. The entire surface is partitioned to a set of adjoining patches represented by distinct species or populations, with phenotypes corresponding to different polynomial functionals. The credit assignment functions take into account both self and symbiotic terms in an adaptive and dynamic manner, in order to produce disparity patches that are fit within their own domain and at the same time fit in association with their symbionts. This persistent propagation of local interactions to a global scale throughout evolution generates a unified disparity surface composed of the many smaller patch surfaces.

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Section: Previous Coevolutionary Paradigmsmentioning

confidence: 99%