Truong Q. Nguyen

University of California, San Diego, San Diego, CA, United States

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Publications (40)54.8 Total impact

  • Source
    Natan Jacobson, Truong Q Nguyen
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    ABSTRACT: Our understanding of human visual perception has been paramount in the development of tools for digital video processing. For this reason, saliency detection, i.e., the determination of visual importance in a scene, has come to the forefront in recent literature. In the proposed work, a new method for scale-aware saliency detection is introduced. Scale determination is afforded through a scale-space model utilizing color and texture cues. Scale information is fed back to a discriminant saliency engine by automatically tuning center-surround parameters through a soft weighting. Excellent results are demonstrated for the proposed method through its performance against a database of measured human fixations. Further evidence of the proposed algorithm's performance is demonstrated through an application to frame rate upconversion. The ability of the algorithm to detect salient objects at multiple scales allows for class-leading performance both objectively, in terms of peak signal-to-noise ratio/structural similarity index, and subjectively. Finally, the need for operator tuning of saliency parameters is dramatically reduced by the inclusion of scale information. The proposed method is well suited for any application requiring automatic saliency determination for images or video.
    IEEE Transactions on Image Processing 12/2011; 21(4):2198-206. · 3.20 Impact Factor
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    Natan Jacobson, Yoav Freund, Truong Q Nguyen
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    ABSTRACT: We propose a novel online learning-based framework for occlusion boundary detection in video sequences. This approach does not require any prior training and instead "learns" occlusion boundaries by updating a set of weights for the online learning Hedge algorithm at each frame instance. Whereas previous training-based methods perform well only on data similar to the trained examples, the proposed method is well suited for any video sequence. We demonstrate the performance of the proposed detector both for the CMU data set, which includes hand-labeled occlusion boundaries, and for a novel video sequence. In addition to occlusion boundary detection, the proposed algorithm is capable of classifying occlusion boundaries by angle and by whether the occluding object is covering or uncovering the background.
    IEEE Transactions on Image Processing 07/2011; 21(1):252-61. · 3.20 Impact Factor
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    Ha Hoang Kha, Hoang Duong Tuan, Truong Q. Nguyen
    IEEE Transactions on Image Processing 01/2011; 20:586-591. · 3.20 Impact Factor
  • Hong Pan, Yaping Zhu, Liang-Zheng Xia, Truong Q. Nguyen
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    ABSTRACT: Combining advantages of shape and appearance features, we propose a novel model that integrates these two complementary features into a common framework for object categorization and detection. In particular, generic shape features are applied as a prefilter that produces initial detection hypotheses following a weak spatial model, then the learnt class-specific discriminative appearance-based SVM classifier using local kernels verifies these hypotheses with a stronger spatial model and filter out false positives. We also enhance the discriminability of appearance codebooks for the target object class by selecting several most discriminative part codebooks that are built upon a pool of heterogeneous local descriptors, using a classification likelihood criterion. Experimental results show that both improvements significantly reduce the number of false positives and cross-class confusions and perform better than methods using only one cue.
    Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011, May 22-27, 2011, Prague Congress Center, Prague, Czech Republic; 01/2011
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    Yaping Zhu, Natan Jacobson, Hong Pan, Truong Q. Nguyen
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    ABSTRACT: An adaptive spatiotemporal saliency algorithm for video attention detection using motion vector decision is proposed, motivated by the importance of motion information in video sequences for human visual system. This novel system can detect the saliency regions quickly by using only part of the classic saliency features in each iteration. Motion vectors calculated by block matching and optical flow are used to determine the decision condition. When significant motion contrast occurs (decision condition is satisfied), the saliency area is detected by motion and intensity features. Otherwise, when motion contrast is low, color and orientation features are added to form a more detailed saliency map. Experimental results show that the proposed algorithm can detect salient objects and actions in video sequences robustly and efficiently.
    Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011, May 22-27, 2011, Prague Congress Center, Prague, Czech Republic; 01/2011
  • Ha Hoang Kha, Hoang Duong Tuan, Truong Q. Nguyen
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    ABSTRACT: The paper proposes a new approach for the design of linear phase finite impulse response (FIR) filters with discrete coefficient values. This problem is a very hard combinatoric discrete optimization, which results in the prohibitive computational complexity for solution. In this paper, we first explicitly express the discrete coefficients of filters as indefinite quadratic but continuous constraints. We then develop an efficient iterative algorithm to tackle the nonconvex optimization problem to locate optimal discrete filter coefficients. By numerical simulation results, we show that our proposed method significantly outperform the methods using quantized coefficients of filters. We also provide an image sampling application to illustrate the performance of our designed filters.
    18th IEEE International Conference on Image Processing, ICIP 2011, Brussels, Belgium, September 11-14, 2011; 01/2011
  • Jing Zhang, Thinh M. Le, S. H. Ong, Truong Q. Nguyen
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    ABSTRACT: Presuming that human visual perception is highly sensitive to the structural information in a scene, we propose the concept of structural activity (SA) together with a model of SA indicator in a new framework for no-reference (NR) image quality assessment (QA) in this study. The proposed framework estimates image quality based on the quantification of the SA information of different visual significance. We propose some alternative implementations of SA indicator in this paper as examples to demonstrate the effectiveness of the SA-motivated framework. Comprehensive testing demonstrates that the model of SA indicator exhibits satisfactory performance in comparison with subjective quality scores as well as representative full-reference (FR) image quality measures.
    Signal Processing. 01/2011; 91:2575-2588.
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    ABSTRACT: Super-resolution image reconstruction is an important technology in many image processing areas such as image sensing, medical imaging, satellite imaging, and television signal conversion. It is also a key word of a recent consumer HDTV set that utilizes the CELL processor. Among various super-resolution methods, the learning-based method is one of the most promising solutions. The problem of the learning-based method is its enormous computational time for image searching from the large database of training images. We have proposed a new Total Variation (TV) regularization super-resolution method that utilizes a learning-based super-resolution method. We have obtained excellent results in image quality improvement. However, our proposed method needs long computational time because of the learning-based method. In this paper, we examine two methods that reduce the computational time of the learning-based method. The resulting algorithms reduce complexity significantly while maintaining comparable image quality. This enables the adoption of learning-based super-resolution to the motion pictures such as HDTV and internet movies.
    18th IEEE International Conference on Image Processing, ICIP 2011, Brussels, Belgium, September 11-14, 2011; 01/2011
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    Meng-Ping Kao, Truong Q Nguyen
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    ABSTRACT: Motion scalability is designed to improve the coding efficiency of a scalable video coding framework, especially in the medium to low range of decoding bit rates and spatial resolutions. In order to fully benefit from the superiority of motion scalability, a rate-distortion optimized bitstream extractor, which determines the optimal motion quality layer for any specific decoding scenario, is required. In this paper, the determination process first starts off with a brute force searching algorithm. Although guaranteed by the optimal performance within the search domain, it suffers from high computational complexities. Two properties, i.e., the monotonically nondecreasing property and the unimodal property, are then derived to accurately describe the rate-distortion behavior of motion scalability. Based on these two properties, modified searching algorithms are proposed to reduce the complexity (up to five times faster) and to achieve the global optimality, even for those decoding scenarios outside the search domain.
    IEEE Transactions on Image Processing 05/2010; 19(5):1214-23. · 3.20 Impact Factor
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    Vikas Ramachandra, Truong Q. Nguyen
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    ABSTRACT: This paper explores a novel metric which can check the consistency and correctness of a disparity map, and hence validate an interpolated view (or video frame for motion compensated frame interpolation) from the estimated correspondences between two or more input views. The proposed reprojection error metric (REM) is shown to be sufficient for the regions where the observed 3D scene has no occlusions. The metric is completely automatic requiring no human input. We also explain how the metric can be extended to be useful for 3D scenes (or videos) with occlusions. However, the proposed metric does not satisfy necessary conditions. We discuss the issues which arise during the design of a necessary metric, and argue that necessary metrics which work in finite time cannot be designed for checking the validity of a method which performs disparity estimation.
    Proc SPIE 02/2010;
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    ABSTRACT: In this paper, we analyze the reproduction of light fields on multiview 3D displays. A two-way interaction between the input light field signal (which is often aliased) and the interview light leakage in modern multiview 3D displays is characterized in the joint spatio-angular frequency domain. Reconstruction of light fields by all physical 3D displays is prone to light leakage. This means that the reconstruction low pass filter implemented by the display is too broad in the angular domain, which causes loss of image sharpness. The combination of the 3D display point spread function and human visual system provides the narrow band low pass filter which removes spectral replicas in the reconstructed light field on the multiview display. The non-ideality of this filter is corrected with the proposed prefiltering technique.
    Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010, 14-19 March 2010, Sheraton Dallas Hotel, Dallas, Texas, USA; 01/2010
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    Chan-Won Seo, Jung Won Kang, Jong-Ki Han, Truong Q. Nguyen
    IEEE Trans. Circuits Syst. Video Techn. 01/2010; 20:1210-1223.
  • Hu Chen, Meng-Ping Kao, Zhao Liu, Truong Q. Nguyen
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    ABSTRACT: The fully scalable motion model (SMM) is proposed for scalable video codec by taking advantage of motion information scalability. In previous work, SMM has been improved to support hierarchical B frame and bidirectional or multidirectional motion estimation. It yields better results comparing to method using unidirectional motion estimation. However, the process of bidirectional or multidirectional rate distortion optimization motion estimation is very complex and is the most time-consuming task in the encoding process. We present several algorithms to reduce its complexity and show corresponding simulation to compare their performance.
    Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010, 14-19 March 2010, Sheraton Dallas Hotel, Dallas, Texas, USA; 01/2010
  • Hong Pan, Liang-Zheng Xia, Truong Q. Nguyen
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    ABSTRACT: Feature selection is an important issue for object detection. In this paper, we propose an effective wrapper-based feature selection scheme using Binary Particle Swarm Optimization (BPSO) and Support Vector Machine (SVM) for object detection. In our algorithm, Scale-Invariant Feature Transform (SIFT) descriptors in a patch around the keypoints are extracted as the initial feature representations. The initial feature set is fed into the feature selection module in which the BPSO searches the feature space, and a SVM classifier serves as an evaluator for the performance of the feature subset selected by the BPSO. We tested the proposed detection scheme on the UIUC car dataset and our results show that feature selection scheme not only improves the detection accuracy but also enhances the detection efficiency.
    Proceedings of the International Conference on Image Processing, ICIP 2010, September 26-29, Hong Kong, China; 01/2010
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    Dũng T Võ, Truong Q Nguyen, Sehoon Yea, Anthony Vetro
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    ABSTRACT: A fuzzy filter adaptive to both sample's activity and the relative position between samples is proposed to reduce the artifacts in compressed multidimensional signals. For JPEG images, the fuzzy spatial filter is based on the directional characteristics of ringing artifacts along the strong edges. For compressed video sequences, the motion compensated spatiotemporal filter (MCSTF) is applied to intraframe and interframe pixels to deal with both spatial and temporal artifacts. A new metric which considers the tracking characteristic of human eyes is proposed to evaluate the flickering artifacts. Simulations on compressed images and videos show improvement in artifact reduction of the proposed adaptive fuzzy filter over other conventional spatial or temporal filtering approaches.
    IEEE Transactions on Image Processing 07/2009; 18(6):1166-78. · 3.20 Impact Factor
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    Jack Tzeng, Truong Q Nguyen
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    ABSTRACT: The novel field of fluid lens cameras introduces unique image processing challenges. Intended for surgical applications, these fluid optics systems have a number of advantages over traditional glass lens systems. These advantages include improved miniaturization and no moving parts while zooming. However, the liquid medium creates two forms of image degradation: image distortion, which warps the image such that straight lines appear curved, and nonuniform color blur, which degrades the image such that certain color planes appear sharper than others. We propose the use of image processing techniques to reduce these degradations. To deal with image warping, we employ a conventional method that models the warping process as a degree-six polynomial in order to invert the effect. For image blur, we propose an adapted perfect reconstruction filter bank that uses high frequency sub-bands of sharp color planes to improve blurred color planes. The algorithm adjusts the number of levels in the decomposition and alters a prefilter based on crude knowledge of the blurring channel characteristics. While this paper primarily considers the use of a sharp green color plane to improve a blurred blue color plane, these methods can be applied to improve the red color plane as well, or more generally adapted to any system with high edge correlation between two images.
    IEEE Transactions on Image Processing 05/2009; 18(4):729-39. · 3.20 Impact Factor
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    Dung Trung Vo, Truong Q. Nguyen, Sehoon Yea, Anthony Vetro
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    ABSTRACT: A fuzzy filter adaptive to both sample's activity and the relative position between samples is proposed to reduce the artifacts in compressed multidimensional signals. For JPEG images, the fuzzy spatial filter is based on the directional characteristics of ringing artifacts along the strong edges. For compressed video sequences, the motion compensated spatiotemporal filter (MCSTF) is applied to intraframe and interframe pixels to deal with both spatial and temporal artifacts. A new metric which considers the tracking characteristic of human eyes is proposed to evaluate the flickering artifacts. Simulations on compressed images and videos show improvement in artifact reduction of the proposed adaptive fuzzy filter over other conventional spatial or temporal filtering approaches.
    IEEE Transactions on Image Processing 01/2009; 18:1166-1178. · 3.20 Impact Factor
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    Yen-Lin Lee, Truong Q. Nguyen
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    ABSTRACT: In this paper, a fast one-pass processing method with an efficient architecture is proposed for motion compensated frame interpolation (MCFI) in high-definition (HD) videos. Unlike previous works involving high complexity, complicated time-consuming iterations, and less practicability, the proposed method adopts one-pass and low-complexity concept. The proposed method operates a modified fast full-search algorithm, multi-level successive eliminate algorithm (MSEA), in a raster scan order as in the usual block-based processing order in popular codecs, such as H.264/AVC and VC-1. The proposed method analyzes and classifies temporal information to compensate insufficient spatial information based on preprocessed neighboring blocks. According to the analyzed temporal information, our method explores true motion candidates and refines the accuracy of true motions for sub-blocks. When searching motion candidates, the proposed method introduces an adaptive overlapped block matching algorithm called a multi-directional enlarged matching algorithm (MDEMA), and considers different overlapped types based on directions of current sought motion vector in order to enhance the searching accuracy and visual quality. Experimental results show that the proposed algorithm provides better video quality than conventional methods and shows satisfying performance.
    Proceedings of the International Conference on Image Processing, ICIP 2009, 7-10 November 2009, Cairo, Egypt; 01/2009
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    Vikas Ramachandra, Matthias Zwicker, Truong Q. Nguyen
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    ABSTRACT: Multiview 3D displays have to multiplex a set of views on a single LCD panel. Due to this, each view has to be down- sampled by a considerable amount leading to loss of details. In this paper, we extend the seam carving technique for adap- tive resizing of images. It is proposed that the depth informa- tion be used along with the image pixel intensity values for resizing. This results in better resized multiview images. It is clear from the results presented that the object structure is maintained when the proposed method is used as compared to vanilla seam carving.
    Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009, 19-24 April 2009, Taipei, Taiwan; 01/2009
  • Source
    Meng-Ping Kao, Truong Q. Nguyen
    [Show abstract] [Hide abstract]
    ABSTRACT: Motion scalability is designed to improve the coding efficiency of a scalable video coding framework, especially in the medium to low range of decoding bit rates or spatial resolutions. In order to fully benefit from the superiority of motion scalability, a rate-distortion optimized bitstream extractor, which determines the optimal motion quality layer for each decoding scenario, is required. In this paper, the determination process first starts off with a brute force search- ing algorithm. Although guaranteed by the optimal performance within the search domain, it has high computational complexity. Two properties, i.e. the monotonically non-decreasing property and the unimodal property, are then derived to accurately describe the rate-distortion behavior of motion scalability. Based on these two properties, modified searching algorithms are proposed to reduce the complexity by a factor up to 5.
    Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009, 19-24 April 2009, Taipei, Taiwan; 01/2009

Publication Stats

126 Citations
54.80 Total Impact Points

Institutions

  • 2008–2011
    • University of California, San Diego
      • Department of Electrical and Computer Engineering
      San Diego, CA, United States
  • 2003
    • Toyota Technological Institute
      Nagu, Okinawa, Japan
  • 2000
    • Boston University
      • Department of Electrical and Computer Engineering
      Boston, Massachusetts, United States