Hock Soon Seah

Nanyang Normal University, Nan-yang-shih, Henan Sheng, China

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Publications (89)31.65 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: Curve extension is a useful function in CAD systems. Disk B-Spline curve has its distinct advantages in representing a 2D region. This paper presents an algorithm for extending the disk B-Spline curve. A disk Bezier segment is used to construct the extending part and G2-continuity can be used to describe the smoothness of the joint disk. Fairness of the extending disk Bezier segment is achieved by minimizing an energy objective function. New control disks are computed by unclamping algorithm to represent the whole extended disk B-Spline curve. The experimental results demonstrate the effectiveness of our method.
    Proceedings of the 2013 International Conference on Computer-Aided Design and Computer Graphics; 11/2013
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    ABSTRACT: Curve blending is an essential task in geometric modeling, while a ball B-spline curve (BBSC) has its advantages in representing freeform tubular objects. This paper proposes a blending algorithm for ball B-Spline curve with G2 continuity, which is used to describe the smoothness of the joint point. An original BBSC is extended smoothly to join another one, such that no additional blending curve is created and the two original curves are not changed. The shape of the extended curve is then determined by minimizing strain energy. The corresponding scalar function of the control balls is determined through applying G2-continuity conditions to the scalar function. In order to ensure the radii of the control balls are positive, we make a decision about the range of the G2-continuity parameter and then determine it by minimizing the strain energy in the affected area. The experiment results demonstrate our method for blending BBSC is effective. Moreover, some G2 blending results of the BBSC in simulating the tubular objects are given.
    Proceedings of the 2013 International Conference on Computer-Aided Design and Computer Graphics; 11/2013
  • Yaqiong Liu, Hock Soon Seah, Gao Cong
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    ABSTRACT: Given a set of moving clients as well as their friend relationships, a road network, and a distance threshold per friend pair, the proximity detection problem in road networks is to find each pair of friends such that the road network distance between them is within the given threshold. The problem of proximity detection is often encountered in friend-locator applications and massively multiplayer online games. Because of the limited battery power and bandwidth, it is better to develop a solution which incurs less communication cost. Hence, the main objective of this problem is to reduce the total communication cost. However, most of the existing proximity detection solutions focus on the Euclidean space but cannot be used in road network space; the solutions for road networks incur substantial communication costs. Motivated by this, we propose two types of solutions to solve the proximity detection problem in road networks. In the first type of solution, each mobile client is assigned with a mobile region of a fixed size. We design algorithms with a fixed radius for the client and server respectively, with the purpose of reducing unnecessary probing messages and update messages. Second, we present a self-tuning policy to adjust the radius of the mobile region automatically to minimize the communication cost. Experiments show that our second type of solution works efficiently and robust with a much lower communication cost with respect to various parameters. In addition, we present our server-side computational cost optimization techniques to reduce the total computational cost.
    Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems; 11/2013
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    ABSTRACT: In this work, we propose a novel graphic saliency detection method to detect visually salient objects in images rendered from 3D geometry models. Different from existing graphic saliency detection methods, which estimate saliency based on pixel-level contrast, the proposed method detects salient objects by computing object-level contrast. Given a rendered image, the proposed method first extracts dominant colors from each object, and represents each object with a dominant color descriptor (DCD). Saliency of each object is then calculated by measuring the contrast between the DCD of the object and the DCDs of its surrounding objects. We also design a new iterative suppression operator to enhance the saliency result. Compared with existing graphic saliency detection methods, the proposed method can obtain much better performance in salient object detection. We further apply the proposed method to selective image rendering and achieve better performance over the relevant existing algorithm.
    Journal of Visual Communication and Image Representation 01/2013; · 1.20 Impact Factor
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    ABSTRACT: In this work, we propose a method to detect visually salient objects in computer synthesized images from 3D meshes. Different from existing detection methods on graphic saliency which compute saliency based on pixel-level contrast, the proposed method computes saliency by measuring object-level contrast of each object to the other objects in a rendered image. Given a synthesized image, the proposed method first extracts dominant colors from each object, and represents each object with the dominant color descriptor (DCD). Saliency is measured as the contrast between the DCD of the object and the DCDs of its surrounding objects. We evaluate the proposed method on a data set of computer rendered images, and the results show that the proposed method obtains much better performance compared with existing related methods.
    Visual Communications and Image Processing (VCIP), 2013; 01/2013
  • Wei Ming Chiew, Feng Lin, Kemao Qian, Hock Soon Seah
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    ABSTRACT: Modern microscopic volumetric imaging processes lack capturing flexibility and are inconvenient to operate. Additionally, the quality of acquired data could not be assessed immediately during imaging due to the lack of a coherent real-time visualization system. Thus, to eliminate the requisition of close user supervision while providing real-time 3D visualization alongside imaging, we propose and describe an innovative approach to integrate imaging and visualization into a single pipeline called an online incrementally accumulated rendering system. This system is composed of an electronic controller for progressive acquisition, a memory allocator for memory isolation, an efficient memory organization scheme, a compositing scheme to render accumulated datasets, and accumulative frame buffers for displaying non-conflicting outputs. We implement this design using a laser scanning confocal endomicroscope, interfaced with an FPGA prototyping board through a custom hardware circuit. Empirical results from practical implementations deployed in a cancer research center are presented in this paper.
    Computers in Industry 01/2013; · 1.71 Impact Factor
  • Lu Dong, Weisi Lin, Chenwei Deng, Ce Zhu, Hock Soon Seah
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    ABSTRACT: For high-quality image rendering using Monte Carlo methods, a large number of samples are required to be computed for each pixel. Adaptive sampling aims to decrease the total number of samples by concentrating samples on difficult regions. However, existing adaptive sampling schemes haven't fully exploited the potential of image regions with complex structures to the reduction of sample numbers. To solve this problem, we propose to exploit uncertainty masking in adaptive sampling. Experimental results show that incorporation of uncertainty information leads to significant sample reduction and therefore time-savings.
    Circuits and Systems (ISCAS), 2013 IEEE International Symposium on; 01/2013
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    ABSTRACT: Compared to monocular pose tracking, 3D articulated body pose tracking from multiple cameras can better deal with self-occlusions and meet less ambiguities. Though considerable advances have been made, pose tracking from multiple images has not been extensively studied: very seldom existing work can produce a solution comparable to that of a marker-based system which generally can recover accurate 3D full-body motion in real-time. In this paper, we present a multi-view approach to 3D body pose tracking. We propose a pose search method by introducing a new generative sampling algorithm with a refinement step of local optimization. This multi-layer search method does not rely on strong motion priors and generalizes well to general human motions. Physical constraints are incorporated in a novel way and 3D distance transform is employed for speedup. A voxel subject-specific 3D body model is created automatically at the initial frame to fit the subject to be tracked. We design and develop the optimized parallel implementations of time-consuming algorithms on GPU (Graphics Processing Unit) using CUDA (Compute Unified Device Architecture), which significantly accelerates the pose tracking process, making our method capable of tracking full body movements with a maximum speed of 9 fps. Experiments on various 8-camera datasets and benchmark datasets (HumanEva-II) captured by 4 cameras demonstrate the robustness and accuracy of our method.
    IEEE Transactions on Multimedia 01/2013; 15(1):106-119. · 1.75 Impact Factor
  • Zheng Zhang, Hock Soon Seah
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    ABSTRACT: Tracking of 3D human body movement from multiple camera video streams is an important problem in the domain of computer vision. In this paper we perform body pose tracking in 3D space using 3D data reconstructed at every frame. We present an efficient GPU-based method for 3D reconstruction of the real world dynamic scenes. Besides volumetric reconstruction, we propose to compute view-independent 3D optical flow (i.e., scene flow) in combination with volumetric reconstruction, and have attained efficient scene flow estimation using GPU acceleration. Body pose estimation starts from a deterministic prediction based on scene flow, and then uses a multi-layer search algorithm involving stochastic search and local optimization. We design and parallelize the PSO-based (particle swarm optimization) stochastic search algorithm and 3D DT (distance transform) computation of the pose estimation method on GPU. To the end, our system can reach efficient and robust body pose tracking.
    Proceedings of the 2012 IEEE 18th International Conference on Parallel and Distributed Systems; 12/2012
  • Wei Ming Chiew, Feng Lin, Kemao Qian, Hock Soon Seah
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    ABSTRACT: Non-rigid registration is crucial in imaging, in particular, to adjust deformities produced during image acquisition and improve the accuracy of datasets. However, conventional imaging systems lack the desired speed and computational bandwidth for additional non-rigid registration of the deformed images. Therefore, such functionality is usually unavailable in time-critical settings. Expensive computations and memory intensive characteristics of non-rigid image registration algorithms such as the Demons algorithm further limits the realization of such systems. In response, we propose an alternative and efficient custom hardware-based Demons registration algorithm which utilizes pipelined streaming models to minimize memory fetches for computation. Designed for highly customizable hardware, our design only requires single-pass of images to compute the Demons kernel. Implementation results on the Xilinx ML605 FPGA system is presented and quantitatively evaluated in clock cycle counts in contrast with a software-based implementation.
    Proceedings of the 2012 IEEE 14th International Conference on High Performance Computing and Communication & 2012 IEEE 9th International Conference on Embedded Software and Systems; 06/2012
  • Jun Yu, Dongquan Liu, Dacheng Tao, Hock Soon Seah
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    ABSTRACT: How do we retrieve cartoon characters accurately? Or how to synthesize new cartoon clips smoothly and efficiently from the cartoon library? Both questions are important for animators and cartoon enthusiasts to design and create new cartoons by utilizing existing cartoon materials. The first key issue to answer those questions is to find a proper representation that describes the cartoon character effectively. In this paper, we consider multiple features from different views, i.e., color histogram, Hausdorff edge feature, and skeleton feature, to represent cartoon characters with different colors, shapes, and gestures. Each visual feature reflects a unique characteristic of a cartoon character, and they are complementary to each other for retrieval and synthesis. However, how to combine the three visual features is the second key issue of our application. By simply concatenating them into a long vector, it will end up with the so-called "curse of dimensionality," let alone their heterogeneity embedded in different visual feature spaces. Here, we introduce a semisupervised multiview subspace learning (semi-MSL) algorithm, to encode different features in a unified space. Specifically, under the patch alignment framework, semi-MSL uses the discriminative information from labeled cartoon characters in the construction of local patches where the manifold structure revealed by unlabeled cartoon characters is utilized to capture the geometric distribution. The experimental evaluations based on both cartoon character retrieval and clip synthesis demonstrate the effectiveness of the proposed method for cartoon application. Moreover, additional results of content-based image retrieval on benchmark data suggest the generality of semi-MSL for other applications.
    IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics: a publication of the IEEE Systems, Man, and Cybernetics Society 04/2012; 42(5):1413-27. · 3.01 Impact Factor
  • Source
    Budianto Tandianus, Henry Johan, Hock Soon Seah
    Journal of WSCG 01/2012; 20(1):37-46.
  • Zheng Zhang, Hock Soon Seah, Jixiang Sun
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    ABSTRACT: In the fields of computer vision, multiple object tracking is an active research area. It is a challenging problem mainly due to the frequent occlusions and interactions that happen between the multiple targets. We formulate the multiple interaction problem as an optimization problem and explore Particle Swarm Optimization (PSO) algorithm for the optimal solution. To tackle the problem of premature convergence, we present a new hybrid PSO that incorporates a differential evolution mutation operation with a Gaussian based PSO. Furthermore, by exploiting the specific structure of multiple object interactions, we introduce a cooperative strategy into the proposed PSO for more efficient searching and for conquering the curse of dimensionality. With patch-based observation models, our method can robustly handle significant occlusions and interactions.
    Evolutionary Computation (CEC), 2012 IEEE Congress on; 01/2012
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    ABSTRACT: Our research focuses on the problem of path planning, which often occurs in virtual world applications. We propose an automatic generation of enhanced waypoint graph, which is a graph data structure consisting of point nodes, which describe the corner features in the virtual world, as well as edges connecting those nodes. Given a polygon soup representation of a virtual world, for every character radius, the proposed algorithm starts by constructing a discrete distance field, consisting of regularly sampled points in 3D space. Corner detection and clustering are then done with respect to the points whose distance values are slightly larger than the character size to get the waypoints. These waypoints are further sparsely connected using traversability test, taking into account their distances to nearby obstacles. The resulting enhanced waypoint graph is sparse but has regularly distributed edges emanating from each waypoint. In addition, the graph is also able to handle different types of motions for characters with various sizes.
    2012 International Conference on Cyberworlds; 01/2012
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    ABSTRACT: Film-making is a high-investment, high-risk industry. We aim to define a framework to bring about a new socio-cultural phenomenon which we call Social Film-Making, bringing part of the film-making process into the digital home community. A wider group of people can be involved via their digital homes to participate in the various stages of film-making to contribute their creative ideas much like the practice of Wikipedia. By connecting people, we want to transform the film industry into a low-investment, low-risk industry and thus bringing film-making accessible to everyone. In this paper, we present only our work on Social Net Coloring, which is a apart of our Social Film-Making project, to enable project managers and artists to color large amount of digital frames in a web-mediated platform that provides excitement, efficiency and flexibility in the film-making process.
    Digital Home (ICDH), 2012 Fourth International Conference on; 01/2012
  • Minglei Liu, Hock Soon Seah, Ce Zhu, Weisi Lin, Feng Tian
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    ABSTRACT: In this paper, we present a reversible data embedding scheme based on an adaptive edge-directed prediction for images. It is known that the difference expansion is an efficient data embedding method. Since the expansion on a large difference will cause a significant embedding distortion, a location map is usually employed to select small differences for expansion and to avoid overflow/underflow problems caused by expansion. However, location map bits lower payload capacity for data embedding. To reduce the location map, our proposed scheme aims to predict small prediction errors for expansion by using an edge detector. Moreover, to generate a small prediction error for each pixel, an adaptive edge-directed prediction is employed which adapts reasonably well between smooth regions and edge areas. Experimental results show that our proposed data embedding scheme for natural images can achieve a high embedding capacity while keeping the embedding distortion low.
    Signal Processing. 01/2012; 92:819-828.
  • Jun Yu, Dongquan Liu, Dacheng Tao, Hock Soon Seah
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    ABSTRACT: Correspondence construction of objects in key frames is the precondition for inbetweening and coloring in 2-D computer-assisted animation production. Since each frame of an animation consists of multiple layers, objects are complex in terms of shape and structure. Therefore, existing shape-matching algorithms specifically designed for simple structures such as a single closed contour cannot perform well on objects constructed by multiple contours with an open shape. This paper introduces a semisupervised patch alignment framework for complex object correspondence construction. In particular, the new framework constructs local patches for each point on an object and aligns these patches in a new feature space, in which correspondences between objects can be detected by the subsequent clustering. For local patch construction, pairwise constraints, which indicate the corresponding points (must link) or unfitting points (cannot link), are introduced by users to improve the performance of correspondence construction. This kind of input is convenient for animation software users via user-friendly interfaces. A dozen of experimental results on our cartoon data set that is built on industrial production suggest the effectiveness of the proposed framework for constructing correspondences of complex objects. As an extension of our framework, additional shape retrieval experiments on MPEG-7 data set show that its performance is comparable with that of a prominent algorithm published in T-PAMI 2009.
    IEEE Transactions on Image Processing 05/2011; 20(11):3257-69. · 3.20 Impact Factor
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    Wei Ming Chiew, Feng Lin, Kemao Qian, Hock Soon Seah
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    ABSTRACT: Laser scanning confocal endomicroscope (LSCEM) has emerged as an imaging modality which provides non-invasive, in vivo imaging of biological tissue on a microscopic scale. Scientific visualizations for LSCEM datasets captured by current imaging systems require these datasets to be fully acquired and brought to a separate rendering machine. To extend the features and capabilities of this modality, we propose a system which is capable of performing realtime visualization of LSCEM datasets. Using field-programmable gate arrays, our system performs three tasks in parallel: (1) automated control of dataset acquisition; (2) imaging-rendering system synchronization; and (3) realtime volume rendering of dynamic datasets. Through fusion of LSCEM imaging and volume rendering processes, acquired datasets can be visualized in realtime to provide an immediate perception of the image quality and biological conditions of the subject, further assisting in realtime cancer diagnosis. Subsequently, the imaging procedure can be improved for more accurate diagnosis and reduce the need for repeating the process due to unsatisfactory datasets.
    World journal of clinical oncology. 04/2011; 2(4):179-86.
  • Source
    Jun Yu, Hock Soon Seah
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    ABSTRACT: In this paper, a novel method called fuzzy diffusion maps (FDM) is proposed to evaluate cartoon similarity, which is critical to the applications of cartoon recognition, cartoon clustering and cartoon reusing. We find that the features from heterogeneous sources have different influence on cartoon similarity estimation. In order to take all the features into consideration, a fuzzy consistent relation is presented to convert the preference order of the features into preference degree, from which the weights are calculated. Based on the features and weights, the sum of the squared differences (L2) can be calculated between any cartoon data. However, it has been demonstrated in some research work that the cartoon dataset lies in a low-dimensional manifold, in which the L2 distance cannot evaluate the similarity directly. Unlike the global geodesic distance preserved in Isomap, the local neighboring relationship preserved in Locally Linear Embedding, and the local similarities of neighboring points preserved in Laplacian Eigenmaps, the diffusion maps we adopt preserve diffusion distance summing over all paths of length connecting the two data. As a consequence, this diffusion distance is very robust to noise perturbation. Our experiment in cartoon classification using Receiver Operating Curves shows fuzzy consistent relation's excellent performance on weights assignment. The FDM’s performance on cartoon similarity evaluation is tested on the experiments of cartoon recognition and clustering. The results show that FDM can evaluate the cartoon similarity more precisely and stably compared with other methods.
    Journal of Computer Science and Technology 01/2011; 26:203-216. · 0.48 Impact Factor
  • Lu Dong, Weisi Lin, Ce Zhu, Hock Soon Seah
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    ABSTRACT: In this work, a sample rate estimator is proposed for selective graphics rendering so that the samples are allocated such that the best perceived image quality can be achieved under a given sample budget. In the proposed estimator, the sample rate of a pixel is decided by not only the visual attention (VA) level of the region to which the pixel belongs but also the required rendering complexity (RC) level of the pixel. The VA and RC values are determined based on the phase-spectrum of the Fourier transform (PFT). Compared with existing sample rate estimators for selective rendering that only consider the VA information, the proposed estimator helps to produce synthesized images with higher perceived quality using the same number of samples.
    Digest of Technical Papers - IEEE International Conference on Consumer Electronics 01/2011;

Publication Stats

146 Citations
31.65 Total Impact Points

Institutions

  • 2006–2013
    • Nanyang Normal University
      Nan-yang-shih, Henan Sheng, China
  • 1999–2013
    • Nanyang Technological University
      • School of Computer Engineering
      Tumasik, Singapore
  • 2011
    • Xiamen University
      • Department of Computer Science
      Xiamen, Fujian, China