Two-Phase Local Search (TPLS) is a general algorithmic framework for multi-objective optimization. TPLS transforms the multi-objective problem into a sequence of single-objective ones by means of weighted sum aggregations. This paper studies different sequences of weights for defining the aggregated problems for the bi-objective case. In particular, we propose two weight setting strategies that...

We develop a fast phase retrieval method which can utilize a large class of local phaseless correlationbased measurements in order to recover a given signal x ∈ C (up to an unknown global phase) in near-linear O ( d log d ) -time. Accompanying theoretical analysis proves that the proposed algorithm is guaranteed to deterministically recover all signals x satisfying a natural flatness (i.e., non...

This report describes a stereo algorithm which uses estimates of local image phase to calculate a disparity map for stereo images. Phase diierence and local frequency are measured by ltering the stereo images with Gabor lters and their derivatives, and the results are used to calculate the local disparity. Due to the limitations on the possible scale of the measured disparity imposed by the use...

Local feature methods suitable for image feature based object recognition and for the estimation of motion and structure are composed of two steps, namely the ‘where’ and ‘what’ steps. The ‘where’ step (e.g., interest point detector) must select image points that are robustly localizable under common image deformations and whose neighborhoods are relatively informative. The ‘what’ step (e.g., l...