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The elevated lighting demand in tunnel's portal zone to guarantee drivers eye adaptation to the internal luminance has been the subject of previous studies exploring the opportunity to gradually introduce daylight in the threshold zone and thus reduce consumption. A 1:10 scale model of this adaptation zone, called daylight “filter” structure, has been constructed to investigate uniformity and luminance...
Risks of software projects are often ignored and risk analysis is left for later stages of project life-cycle, resulting in serious financial losses. This paper proposes a goal-oriented risk analysis framework that includes inter-dependencies among treatments and risks in terms of likelihood and generate optimal solutions with respect to multiple objectives such as goal rewards, treatment costs, or...
Recurring visual elements in videos commonly represent central content entities, such as main characters and dominant objects. The automated detection of such elements is crucial for various application fields ranging from compact video content summarization to the retrieval of videos sharing common visual entities. Recent approaches for content-based video analysis commonly require for prior knowledge...
The Set Covering Problem is a classical problem in combinatorial optimization that belongs to the Karp's 21 NP-hard problems, with many practical applications. In this paper, an approach based on Black Hole Algorithm is proposed to solve this problem. The black hole algorithm is a metaheuristic that is inspired by nature, especially by the black hole phenomenon in space. To improve the performance...
In SLAM systems, loop closures play crucial role to decrease the accumulating drift of the estimated trajectory for consistent mapping. Place recognition is so important for determining loop closure candidates. This paper presents a method for visual place recognition using image histograms in conjunction with keypoint correspondences to select loop closure candidates. The method compares color and...
In soccer matches, 3D reconstruction is a main part of many applications including free-viewpoint broadcasting, match analysis, augmented reality, and refereeing examination. The main challenge of 3D reconstruction in soccer scenes is the human body reconstruction. Although 3D reconstruction methods have been improved to a high extent in controlled condition, still there are lots of uncovered issues...
In this paper, an optimization method using Particle Swarm Optimization (PSO) is proposed for the power/ground (P/G) pin assignment of large-scale high-pin-count ball grid array (BGA) packages. A general PSO working flow is introduced, and two examples of P/G pin assignment using the proposed method are presented. For validation, a comparison between Xilinx product and the result from PSO is presented...
Particle filters perform the nonlinear estimation and have been proven to be a powerful tool in solving visual tracking problems. However, the problem of sample impoverishment is still a drawback of particle filter. To solve this problem, a bat-inspired particle filter is proposed in this work. The particles in the particle filter are optimized using a new biologically inspired optimization algorithm,...
We propose a power-constrained image enhancement system to maintain human visual perception when the LCD or LED display is under low backlight. Adopting the low backlight mode can save the electricity and lengthen the battery using time. First, we deduce the relationship between the image and the backlight for maintaining the same visual perceptual quality. Then, we propose a sparsity-based image...
In this paper, we propose a novel channel impulse response (CIR) clustering algorithm using a sparsity-based method, which exploits the feature of CIR that power of multipath component (MPC) is exponentially decreasing with increasing delay. We first use a sparsity-based optimization to recover CIRs, which can be well solved by using reweighted L1 minimization. Then a heuristic approach is provided...
In wireless visual sensor networks comprised of multiple camera-enabled sensors, source prioritization can be exploited to soften the impact of congestion, packet loss and energy depletion when higher relevant packets are processed. However, for such optimizations, source nodes have to be properly prioritized according to some effective metric. When performing visual sensing over moving targets, sensors...
Gamification is a recent phenomenon that emphasizes the process of incorporating game elements, for a specific purpose, into an existing system in order to maximise a user's experience and increase engagement with the system. In this paper, we discuss the effects of the introduction of the principles of gamification to a system for solving real-world container loading problems in a warehouse environment...
The deep learning of neural network works on vision recognition and classification tasks briskly, and it can extract great features of an image for classification. Recently, many approaches have studied the visual tracking in two-ways with these characteristics. First, they can regard tracking problem as classifying each video and frame by learning all dataset. Second, use the deep neural network...
Recently, deep Convolutional Neural Networks (CNNs) have been used to achieve state-of-the-art performance on a wide range of visual learning tasks. However, when facing some imbalanced learning tasks where the training samples are unevenly distributed among different classes, CNNs tend to produce performance bias toward the majority class, making them not suitable for applications in which the recognition...
Content based image retrieval has become one of the prominent research topic because of the proliferation of video and image data in digital form. Color, texture and shape are useful to represent and compare images automatically. In this paper we apply Fourier transform based saliency approach for image retrieval and compare the results with some of the existing techniques. Experimental results are...
HEVC, as the latest video coding standard, achieves top performance on image compression. On the basis of this, we propose a novel approach to optimize subjective quality for HEVC-based image compression. Specifically, a bit allocation formulation is established to optimize subjective quality with constraint on bit-rates. Then, we propose a recursive Taylor expansion method to quickly solve such a...
Visual feature descriptors have been successfully deployed in a wide range of applications, e.g. visual retrieval and analysis. To transmit these descriptors over bandwidth-limited networks, a high effciency feature coding technique is highly desired to maximize compression capability and achieve compact feature representations. In this paper, a hybrid visual feature descriptor compression framework...
Exploiting contextual cues has been a key idea to improve people detection in crowded scenes. Along this line we present a novel context-driven approach to detect people in crowded scenes. Based on a context graph that incorporates both geometric and social contextual patterns in crowds, we apply label propagation to discover weak detections contextually compatible with true detections while suppressing...
Multi-target tracking (MTT) is the task of localizing objects of interest in a video and associating them through time. Accurate affinity measures between object detections is crucial for MTT. Previous methods use simple affinity measures, based on heuristics, that are unable to track through occlusions and missing detections. To address this problem, this paper proposes a novel affinity measure by...
Traveling salesman problem (TSP) which is a classic combinational optimization problem has a wide range of applications in many areas. Many researchers focus on this problem and propose several algorithms. However, it was proved to be NP-hard, which is very difficult to be solved. No algorithm can solve any types of this problem effectively. In order to propose an effective algorithm for TSP, this...
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