64,171 research outputs found
3-D Hand Pose Estimation from Kinect's Point Cloud Using Appearance Matching
We present a novel appearance-based approach for pose estimation of a human
hand using the point clouds provided by the low-cost Microsoft Kinect sensor.
Both the free-hand case, in which the hand is isolated from the surrounding
environment, and the hand-object case, in which the different types of
interactions are classified, have been considered. The hand-object case is
clearly the most challenging task having to deal with multiple tracks. The
approach proposed here belongs to the class of partial pose estimation where
the estimated pose in a frame is used for the initialization of the next one.
The pose estimation is obtained by applying a modified version of the Iterative
Closest Point (ICP) algorithm to synthetic models to obtain the rigid
transformation that aligns each model with respect to the input data. The
proposed framework uses a "pure" point cloud as provided by the Kinect sensor
without any other information such as RGB values or normal vector components.
For this reason, the proposed method can also be applied to data obtained from
other types of depth sensor, or RGB-D camera
Towards building information modelling for existing structures
The transformation of cities from the industrial age (unsustainable) to the knowledge age (sustainable) is essentially a âwhole life cycleâ process consisting of; planning, development, operation, reuse and renewal. During this transformation, a multi-disciplinary knowledge base, created from studies and research about the built environment aspects is fundamental: historical, architectural, archeologically, environmental, social, economic, etc is critical. Although there are a growing number of applications of 3D VR modelling applications, some built environment applications such as disaster management, environmental simulations, computer aided architectural design and planning require more sophisticated models beyond 3D graphical visualization such as multifunctional, interoperable, intelligent, and multi-representational.
Advanced digital mapping technologies such as 3D laser scanner technologies can be are enablers for effective e-planning, consultation and communication of usersâ views during the planning, design, construction and lifecycle process of the built environment. For example, the 3D laser scanner enables digital documentation of buildings, sites and physical objects for reconstruction and restoration. It also facilitates the creation of educational resources within the built environment, as well as the reconstruction of the built environment. These technologies can be used to drive the productivity gains by promoting a free-flow of information between departments, divisions, offices, and sites; and between themselves, their contractors and partners when the data captured via those technologies are processed and modelled into BIM (Building Information Modelling). The use of these technologies is key enablers to the creation of new approaches to the âWhole Life Cycleâ process within the built and human environment for the 21st century. The paper describes the research towards Building Information Modelling for existing structures via the point cloud data captured by the 3D laser scanner technology. A case study building is elaborated to demonstrate how to produce 3D CAD models and BIM models of existing structures based on designated technique
Bid-Centric Cloud Service Provisioning
Bid-centric service descriptions have the potential to offer a new cloud
service provisioning model that promotes portability, diversity of choice and
differentiation between providers. A bid matching model based on requirements
and capabilities is presented that provides the basis for such an approach. In
order to facilitate the bidding process, tenders should be specified as
abstractly as possible so that the solution space is not needlessly restricted.
To this end, we describe how partial TOSCA service descriptions allow for a
range of diverse solutions to be proposed by multiple providers in response to
tenders. Rather than adopting a lowest common denominator approach, true
portability should allow for the relative strengths and differentiating
features of cloud service providers to be applied to bids. With this in mind,
we describe how TOSCA service descriptions could be augmented with additional
information in order to facilitate heterogeneity in proposed solutions, such as
the use of coprocessors and provider-specific services
Computing resource allocation in three-tier IoT fog networks: a joint optimization approach combining Stackelberg game and matching
Fog computing is a promising architecture to
provide economical and low latency data services for future
Internet of Things (IoT)-based network systems. Fog computing
relies on a set of low-power fog nodes (FNs) that are located
close to the end users to offload the services originally targeting
at cloud data centers. In this paper, we consider a specific
fog computing network consisting of a set of data service operators
(DSOs) each of which controls a set of FNs to provide the
required data service to a set of data service subscribers (DSSs).
How to allocate the limited computing resources of FNs to all
the DSSs to achieve an optimal and stable performance is an
important problem. Therefore, we propose a joint optimization
framework for all FNs, DSOs, and DSSs to achieve the optimal
resource allocation schemes in a distributed fashion. In the
framework, we first formulate a Stackelberg game to analyze
the pricing problem for the DSOs as well as the resource allocation
problem for the DSSs. Under the scenarios that the DSOs
can know the expected amount of resource purchased by the
DSSs, a many-to-many matching game is applied to investigate
the pairing problem between DSOs and FNs. Finally, within the
same DSO, we apply another layer of many-to-many matching
between each of the paired FNs and serving DSSs to solve
the FN-DSS pairing problem. Simulation results show that our
proposed framework can significantly improve the performance
of the IoT-based network systems
T-spline based unifying registration procedure for free-form surface workpieces in intelligent CMM
With the development of the modern manufacturing industry, the free-form surface is widely used in various fields, and the automatic detection of a free-form surface is an important function of future intelligent three-coordinate measuring machines (CMMs). To improve the intelligence of CMMs, a new visual system is designed based on the characteristics of CMMs. A unified model of the free-form surface is proposed based on T-splines. A discretization method of the T-spline surface formula model is proposed. Under this discretization, the position and orientation of the workpiece would be recognized by point cloud registration. A high accuracy evaluation method is proposed between the measured point cloud and the T-spline surface formula. The experimental results demonstrate that the proposed method has the potential to realize the automatic detection of different free-form surfaces and improve the intelligence of CMMs
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