共查询到20条相似文献,搜索用时 453 毫秒
1.
The paper presents a real-time algorithm that compensates image distortions due to atmospheric turbulence in video sequences,
while keeping the real moving objects in the video unharmed. The algorithm involves (1) generation of a “reference” frame,
(2) estimation, for each incoming video frame, of a local image displacement map with respect to the reference frame, (3)
segmentation of the displacement map into two classes: stationary and moving objects; (4) turbulence compensation of stationary
objects. Experiments with both simulated and real-life sequences have shown that the restored videos, generated in real-time
using standard computer hardware, exhibit excellent stability for stationary objects while retaining real motion.
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2.
We present a framework that uses data dependency information to automate load balanced volume distribution and ray-task scheduling
for parallel visualization of massive volumes. This dependency graph approach improves load balancing for both ray casting
and ray tracing. The main bottlenecks in distributed volume rendering involve moving data across the network and loading memory
into rendering hardware. Our load balancing solution combines static network distribution with dynamic ray-task scheduling.
At the core of the dependency graph approach are the flex-block tree, introduced in this paper, and the cell-tree. The flex-block
tree is similar to a kd-tree except that leaf nodes are cells containing a combination of empty space and tightly cropped
subvolumes, or flex-blocks. A main contribution of this paper is the moving walls algorithm, which uses dynamic programming to create a flex-block partition. We show results for optimizing distributed ray
cast rendering using a time cost function. We compare data distribution using the moving walls algorithm, with distribution
using a recursive solution, and with a grid combined with a local kd-tree partition on each render-node.
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3.
An interconnection network architecture that promises to be an interesting option for future-generation parallel processing
systems is the OTIS (Optical Transpose Interconnection System) optoelectronic architecture. Therefore, all performance improvement
aspects of such a promising architecture need to be investigated; one of which is load balancing technique. This paper focuses
on devising an efficient algorithm for load balancing on the promising OTIS-Hypercube interconnection networks. The proposed
algorithm is called Clusters Dimension Exchange Method (CDEM). The analytical model and the experimental evaluation proved
the excellence of OTIS-Hypercube compared to Hypercube in terms of various parameters, including execution time, load balancing
accuracy, number of communication steps, and speed.
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4.
With the rapid advancements in positioning technologies such as the Global Positioning System (GPS) and wireless communications,
the tracking of continuously moving objects has become more convenient. However, this development poses new challenges to
database technology since maintaining up-to-date information regarding the location of moving objects incurs an enormous amount
of updates. Existing indexes can no longer keep up with the high update rate while providing speedy retrieval at the same
time. This study aims to improve k nearest neighbor (kNN) query performance while reducing update costs. Our approach is based
on an important observation that queries usually occur around certain places or spatial landmarks of interest, called reference
points. We propose the Reference-Point-based tree (RP-tree), which is a two-layer index structure that indexes moving objects
according to reference points. Experimental results show that the RP-tree achieves significant improvement over the TPR-tree.
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5.
The objective of this paper is to present an overall approach to forecasting the future position of the moving objects of
an image sequence after processing the images previous to it. The proposed method makes use of classical techniques such as
optical flow to extract objects’ trajectories and velocities, and autoregressive algorithms to build the predictive model.
Our method can be used in a variety of applications, where videos with stationary cameras are used, moving objects are not
deformed and change their position with time. One of these applications is traffic control, which is used in this paper as
a case study with different meteorological conditions to compare with.
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6.
In this paper, we present an Inverse Multi-Objective Robust Evolutionary (IMORE) design methodology that handles the presence
of uncertainty without making assumptions about the uncertainty structure. We model the clustering of uncertain events in
families of nested sets using a multi-level optimization search. To reduce the high computational costs of the proposed methodology
we proposed schemes for (1) adapting the step-size in estimating the uncertainty, and (2) trimming down the number of calls
to the objective function in the nested search. Both offline and online adaptation strategies are considered in conjunction
with the IMORE design algorithm. Design of Experiments (DOE) approaches further reduce the number of objective function calls
in the online adaptive IMORE algorithm. Empirical studies conducted on a series of test functions having diverse complexities
show that the proposed algorithms converge to a set of Pareto-optimal design solutions with non-dominated nominal and robustness
performances efficiently.
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7.
Data gathering is a major function of many applications in wireless sensor networks (WSNs). The most important issue in designing
a data gathering algorithm is how to save energy of sensor nodes while meeting the requirement of applications/users such
as sensing area coverage. In this paper, we propose a novel hierarchical clustering protocol (DEEG) for long-lived sensor
network. DEEG achieves a good performance in terms of lifetime by minimizing energy consumption for in-network communications
and balancing the energy load among all the nodes, the proposed protocol achieves a good performance in terms of network lifetime.
DEEG can also handle the energy hetergenous capacities and guarantee that out-network communications always occur in the subregion
with high energy reserved. Furthermore, it introduces a simple but efficient approach to cope with the area coverage problem.
We evaluate the performance of the proposed protocol using a simple temperature sensing application. Simulation results show
that our protocol significantly outperforms LEACH and PEGASIS in terms of network lifetime and the amount of data gathered.
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8.
This paper introduces the problem of discovering maximum-length repeating patterns in music objects. A novel algorithm is
presented for the extraction of this kind of patterns from a melody music object. The proposed algorithm discovers all maximum-length
repeating patterns using an “aggressive” accession during searching, by avoiding costly repetition frequency calculation and
by examining as few as possible repeating patterns in order to reach the maximum-length repeating pattern(s). Detailed experimental
results illustrate the significant performance gains due to the proposed algorithm, compared to an existing baseline algorithm.
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9.
Due to the popularity of location-based services, determining the location of a device at all times has become a subject of
great interests. Although many GPS-based applications have been developed and successfully deployed in various fields, their
applicabilities are hindered by the obstruction of the objects in the environment. Essentially, as satellite signals cannot
penetrate the walls of buildings, the coverage of GPS systems is limited to outdoor environments. To fully exploit the benefit
of location-based services, approaches that determine the location of a device in indoor environments need to be established.
This study presents a novel location determination mechanism that uses an indoor WLAN and back-propagation neural network
(BPN). A museum is taken as the context of the example indoor environment. Location determination is achieved using the combined
strengths of 802.11b wireless access signals. With a significant number of access points (APs) installed in the museum, hand-held
devices can sense the strengths of the signals from all APs to which the devices can connect. Using a back-propagation network,
device locations can be estimated with sufficient accuracy. A novel adaptive algorithm is implemented for enhancing the accuracy
of the estimation.
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10.
Mobile sinks can be used to balance energy consumption for sensor nodes in Wireless Sensor Networks (WSNs). Mobile sinks are
required to inform sensor nodes about their new location information whenever necessary. However, frequent location updates
from mobile sinks can lead to both rapid energy consumption of sensor nodes and increased collisions in wireless transmissions.
We propose a new solution with adaptive location updates for mobile sinks to resolve this problem. When a sink moves, it only
needs to broadcast its location information within a local area other than among the entire network. Both theoretical analysis
and simulation studies show that this solution consumes less energy in each sensor node and also decreases collisions in wireless
transmissions, which can be used in large-scale WSNs.
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11.
In this article we present the parallelisation of an explicit-state CTL * model checking algorithm for a virtual shared-memory high-performance parallel machine architecture. The algorithm uses a combination of private and shared data structures for implicit and dynamic load balancing with minimal synchronisation overhead. The performance of the algorithm and the impact that different design decisions have on the performance are analysed using both mathematical cost models and experimental results. The analysis shows not only the practicality and effective speedup of the algorithm, but also the main pitfalls of parallelising model checking for shared-memory architectures. 相似文献
12.
The objective measurement of blocking artifacts plays an important role in the design, optimization, and assessment of image
and video compression. In this paper, we propose a novel measurement algorithm for blocking artifacts. Computer simulation
results indicate that the proposed method accurately measures the blocking artifacts without using the original image. Moreover,
the proposed algorithm can be easily implemented in both pixel and DCT domains.
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13.
Tracking location is challenging due to the numerous constraints of practical systems including, but not limited to global
cost, device volume and weight, scalability and accuracy; these constraints are typically more severe for systems that should
be wearable and used indoors. We investigate the use of wearable solar cells to track changing light conditions (a concept
that we named LuxTrace) as a source of user displacement and activity data. We evaluate constraints of this approach and present
results from an experimental validation of displacement and activity estimation. The results indicate that a distance estimation
accuracy of 21 cm (80% quantile) can be achieved. A simple method to combine LuxTrace with complementary absolute location
estimation methods is also presented. We apply carpet-like distributed RFID tags to demonstrate online learning of new lighting
environments.
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14.
In this paper, we propose a salient human detection method that uses pre-attentive features and a support vector machine (SVM)
for robot vision. From three pre-attentive features (color, luminance and motion), we extracted three feature maps and combined
them as a salience map. By using these features, we estimated a given object’s location without pre-assumptions or semi-automatic
interaction. We were able to choose the most salient object even if multiple objects existed. We also used the SVM to decide
whether a given object was human (among the candidate object regions). For the SVM, we used a new feature extraction method
to reduce the feature dimensions and reflect the variations of local features to classifiers by using an edged-mosaic image.
The main advantage of the proposed method is that our algorithm was able to detect salient humans regardless of the amount
of movement, and also distinguish salient humans from non-salient humans. The proposed algorithm can be easily applied to
human robot interfaces for human-like vision systems.
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15.
This paper describes the simulated car racing competition that was arranged as part of the 2007 IEEE Congress on Evolutionary
Computation. Both the game that was used as the domain for the competition, the controllers submitted as entries to the competition
and its results are presented. With this paper, we hope to provide some insight into the efficacy of various computational
intelligence methods on a well-defined game task, as well as an example of one way of running a competition. In the process,
we provide a set of reference results for those who wish to use the simplerace game to benchmark their own algorithms. The paper is co-authored by the organizers and participants of the competition.
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16.
This paper proposes an appearance generative mixture model based on key frames for meanshift tracking. Meanshift tracking
algorithm tracks an object by maximizing the similarity between the histogram in tracking window and a static histogram acquired
at the beginning of tracking. The tracking therefore could fail if the appearance of the object varies substantially. In this
paper, we assume the key appearances of the object can be acquired before tracking and the manifold of the object appearance
can be approximated by piece-wise linear combination of these key appearances in histogram space. The generative process is
described by a Bayesian graphical model. An Online EM algorithm is proposed to estimate the model parameters from the observed
histogram in the tracking window and to update the appearance histogram. We applied this approach to track human head motion
and to infer the head pose simultaneously in videos. Experiments verify that our online histogram generative model constrained
by key appearance histograms alleviates the drifting problem often encountered in tracking with online updating, that the
enhanced meanshift algorithm is capable of tracking object of varying appearances more robustly and accurately, and that our
tracking algorithm can infer additional information such as the object poses.
Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.
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17.
Moving point object data can be analyzed through the discovery of patterns in trajectories. We consider the computational
efficiency of detecting four such spatio-temporal patterns, namely flock, leadership, convergence, and encounter, as defined
by Laube et al., Finding REMO—detecting relative motion patterns in geospatial lifelines, 201–214, ( 2004). These patterns are large enough subgroups of the moving point objects that exhibit similar movement in the sense of direction,
heading for the same location, and/or proximity. By the use of techniques from computational geometry, including approximation
algorithms, we improve the running time bounds of existing algorithms to detect these patterns.
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18.
Quantitative usability requirements are a critical but challenging, and hence an often neglected aspect of a usability engineering process. A case study is described where quantitative usability requirements played a key role in the development of a new user interface of a mobile phone. Within the practical constraints of the project, existing methods for determining usability requirements and evaluating the extent to which these are met, could not be applied as such, therefore tailored methods had to be developed. These methods and their applications are discussed. 相似文献
19.
We define a new birth and death dynamics dealing with configurations of disks in the plane. We prove the convergence of the
continuous process and propose a discrete scheme converging to the continuous case. This framework is developed to address
image processing problems consisting in detecting a configuration of objects from a digital image. The derived algorithm is
applied for tree crown extraction and bird detection from aerial images. The performance of this approach is shown on real
data.
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20.
Listening to music on personal, digital devices whilst mobile is an enjoyable, everyday activity. We explore a scheme for
exploiting this practice to immerse listeners in navigation cues. Our prototype, ONTRACK, continuously adapts audio, modifying
the spatial balance and volume to lead listeners to their target destination. First we report on an initial lab-based evaluation
that demonstrated the approach’s efficacy: users were able to complete tasks within a reasonable time and their subjective
feedback was positive. Encouraged by these results we constructed a handheld prototype. Here, we discuss this implementation
and the results of field-trials. These indicate that even with a low-fidelity realisation of the concept, users can quite
effectively navigate complicated routes.
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