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This paper proposes a novel method of tracing dynamic objects for indoor mobile robot by fusing visual features. The proposed tracking algorithm is a kind of improved CAMSHIFT algorithm combined with SURF, optical flow and ultra-sonic data, to enhance the tracking capability. Since CAMSHIFT algorithm is based HSV color space model, it is weak on strong lighting, abrupt change of light and fast-moving...
The major design challenges of ASIC design, like power dissipation, timing, voltage-drop, interconnect and reliability are tackled during the Physical Design phase of any flow. The placement procedure can significantly modify parts of the design and consequently metrics relevant to the aforementioned challenges. Text reports cannot always generate useful insight based solely on these metrics. Design...
In conventional visual odometry (VO) systems, perspective-n-point (PnP) method and random sample consensus (RANSAC) algorithm are generally used to estimate camera poses. However, heavy computational burden is incurred, and the pose estimations are not reliable as well. Therefore, in this paper, an improved VO system is proposed, where an off-line camera calibration method is used to obtain lesser...
Simulating real world applications containing many functionalities using programs tend to become very complex in structure and behaviour. Validating such programs for its correctness require correct outputs and their ability to cope with erroneous scenarios. This work proposes a methodology for the verification of such programs defined using Java, based on their design-time and run-time model, where...
The WRGB-OLED with larger-sized display resolution can bring us more colorful and better visual experiences. However, it also makes OLED display system suffer from a serious bottleneck on memory bandwidth. In this paper, the lossless pixel-gradient EC algorithm is proposed to overcome this bottleneck. It consists of two core techniques: Finer-Gradient-Based Prediction (FGBP) and Gradient-Based Golomb-Rice...
In Gradient-Based Cross-Spectral Stereo Matching (GB-CSSM) output disparity maps tend to produce coarse results that are, for the most part, reliable. However, general methods of improving the performance of disparity maps generated from the Cross-Spectral comparison of visual and full infrared input images are non-existent. In particular, previous works fail to address the role and interaction of...
Clustering techniques have gained great popularity in neuroscience data analysis especially in analysing data from complex experiment paradigm where it is hard to apply traditional model-based method. However, when employing clustering analysis, many clustering algorithms are available nowadays and even with an individual clustering algorithm, choices like parameter settings and distance metrics are...
As eye tracking is becoming available in wearable or portable devices, eye movement (EM) analysis will be used to provide real time alerts, feedback, and/or assistive information for diversified objectives when performing tasks. However, we lack the methodologies to effectively analyze real time EM attributes including eye fixation numbers, durations, and especially visual scanpath sequences (i.e...
Mass casualty events caused by a biological weapon require fully capable first response teams. However, human first responders are equipped with protective gear, which limits their capabilities to complete tasks. Robots can be employed to work collaboratively with the first responders in order to augment the human's reduced abilities. The robot needs to understand and adapt to the human's workload...
The following paper presents a new approach for analyzing learning style at the beginning of course. Learner styles, learning style models and existing methods to identify learning style are explained. With proper using of Item Response Theory for determining learner style, greater impact on learning experience can be achieved, such as personalized learning, effective learning as well high satisfaction...
Structured output support vector machine (SVM) based tracking algorithms have shown favorable performance recently. Nonetheless, the time-consuming candidate sampling and complex optimization limit their real-time applications. In this paper, we propose a novel large margin object tracking method which absorbs the strong discriminative ability from structured output SVM and speeds up by the correlation...
This paper is an exhibition of graph matchingresults, in a classification context. We present Photo(Graph) Gallery, a platform that allows one to visually interpret graphmatchings. We aim at understanding the computed matchingsin order to improve the rates of graph classification. Preliminaryresults of the study performed on two data sets are also illustrated. Furthermore, a demonstrator of our proof-of-concept...
We investigate the problem of analyzing word frequencies in multiple text sources with the aim to give an overview of word-based similarities in several texts as a starting point for further analysis. To reach this goal, we designed a visual analytics approach composed of typical stages and processes, combining algorithmic analysis, visualization techniques, the human users with their perceptual abilities,...
The paper reports comparative performances of five distinct algorithms used for rain removal from single images. Both synthetic and real images are considered, while taking into account standard figures of merit such as PSNR, VIF and SSIM. The experiments revealed that the Gaussian Mixture Model based approach yields best performances in terms of visual quality.
In daily life it is necessary to learn skills that can be applied in different tasks and different contexts. Usually these skills are acquired by observation or by direct physical training with another expert person. The critical point is to know which is the best possible way to achieve this knowledge acquisition. In this work we have proposed a collaborative environment where subjects with different...
Node removal is a phenomenon occurs frequently in various organizational networks and it is important for a network to re-organize into a new network so as to maintain its function. In this paper, we focus primarily on the Organizational Network Reshaping Problem: when a node is removed from the network, which node will take its place and how the network will reshape. According to different organizational...
AGV path planning problems play an extremely important role in navigations of AGV. Intelligence algorithms provide an effective way to solve such complicated problems. Artificial fish swarm algorithm (AFSA) is a newly proposed promising swarm intelligence optimization algorithm, yet there still exist some disadvantages of it, such as low optimization precision and convergence rate. Aiming at these...
An uncertainty quantification approach to estimate the errors incurred by the Kanade Lucas Tomasi (KLT) feature tracking algorithm is presented. The covariance analysis is based on the linearized sensitivity calculations of the KLT algorithm. Track uncertainty thus computed is utilized to quantify the errors associated with feature based relative pose estimation algorithms. This paper also show that...
In order to shorten the required time for the analysis of medical substances, Digital Microfluidic Biochips (DMFBs) have been suggested. They allow for handling small amounts of samples and reagents on a circuit board and, thus, automatically execute medical experiments that are usually conducted manually in laboratories. However, there are various challenges in the design of DMFBs. Issues such as...
With more proliferation of services and higher degree of personalization, higher accurate approaches to service recommendation are becoming more and more pivotal. Performance of existing service recommendation approaches is not satisfactory due to the sparseness of available data set or the incomplete information of the global service market, which make it difficult to identify a customer's potential...
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