Feature Matching of Multi-View 3d Models Based on Hash Binary Encoding

Abstract

Technology has undergone rapid development in the past several decades and we are now at a point where many technologies are available to help create smart cities. Many technology companies and research institutions as well as political organizations are currently discussing this field with the highest priority. One can say that the biggest challenge to smart cities is not technologies themselves, but the merging of all available technologies into one symbiotic unit that fulfills the expected objectives. Smart cities are about connecting subsystems, sharing and evaluating data, and providing quality of life and satisfaction to citizens. We have various models of transportation systems, optimizations of energy usage, street lighting systems, building management systems, urban transport optimizations, however currently, such models are dealt with separately. In this paper, we provide an overview of the smart city concept and discuss why Multi-agent systems are the right tool for the modeling of smart cities. The biggest challenge is in connecting and linking particular subsystems within a smart city. In this paper, a modeling of a smart city building blocks is provided and demonstrated with one particular example -a smart street lighting system. Focus will be on the decomposition of the system into subsystems as well as a description of particular modules. We propose to build models and since each individual entity can be modeled as an agent with its beliefs, desires and intentions, we suggest using Multi-agent systems as a tool for modeling systems' connections within the smart city and assessing how best to use the data from those systems.

Distributed Cluster Based 3D Model Retrieval with Map-Reduce

“…In this Section, we will briefly review the works about view-based 3D model retrieval. Recently, view-based methods attracted much more attention due to it independent of 3D models, and can be realized simply with multi-view representation of models [8]. Typically, there are two key steps in this technology.…”

Load Balancing Based on Firefly and Ant Colony Optimization Algorithms for Parallel Computing

“…They are applied to solve various optimization scheduling problems and are widely used in industry [ 6 ], network transmission [ 7 ], biology [ 8 ] and cloud computing [ 9 ]. Among them, the combination of neural networks and other algorithms has achieved considerable research success in image capture and retrieval [ 10 , 11 , 12 , 13 ]. With the development of parallel computing, the improvement and optimization of heuristic algorithms to solve the load-balancing problem of parallel computing have also achieved considerable results.…”

A Semi-automatic 3D mesh segmentation based on Cross-Boundary strokes

“…In geometric processing and shape understanding, 3D object segmenting is a fundamental problem. It performs an important role in assisting parametrization, texture mapping Sander et al [1], shape matching, 3D shape modelling [2], 3D model generation Li et al [3], animation [4], mesh parameterization [5,6], 3D models feature matching [7], deformation [8,9], 3D object retrieval [10,11,12], compression [13], etc. Mesh segmentation aims to decompose a mesh, representing a 3D object, into parts.…”