Localization of Cross-Junctions in Warehouse Beam Structure by Supervised Descent Method

University essay from Högskolan i Halmstad/Akademin för informationsteknologi

Author: Sepideh Ghorbanloo; [2016]

Keywords: ;

Abstract:

A new application of the Supervised Descent Method (SDM) [26] optimization

algorithm in order to find solutions for modeling a structured

environment such as a warehouse is investigated in this work.

For modeling a structured warehouse, a large number of front-view

images of a warehouse are collected. This work investigates basic

computational elements for building a two-dimensional map of the

warehouse by the SDM algorithm suggesting to use a well-known

technique as feature extraction, i.e. Scale Invariant Feature Transform

(SIFT) [16]. The ground-truths are extracted manually on pillar-beam

intersections from real-world warehouse images. To address the problem

of modeling a warehouse, different modeling scenarios ranging

from a complex to a simple model each with increasing the initial

suggested displacement are investigated. As an important contribution,

this work reports statistics concerning the divergence rate of

SDM (combined with SIFT) performance in all scenarios for both

sides of corridors of the warehouse images. This work has shown

that the SDM transformation method in its original form is not sufficient

enough to be used in general visual object location problems.

  AT THIS PAGE YOU CAN DOWNLOAD THE WHOLE ESSAY. (follow the link to the next page)