Yong-Jin Liu

Image retargeting quality assessment

Content‐aware image retargeting is a technique that can flexibly display images with different aspect ratios and simultaneously preserve salient regions in images. Recently many image retargeting techniques have been proposed. To compare image quality by different retargeting methods fast and reliably, an objective metric simulating the human vision system (HVS) is presented in this paper. Different from traditional objective assessment methods that work in bottom‐up manner (i.e., assembling pixel‐level features in a local‐to‐global way), in this paper we propose to use a reverse order (top‐down manner) that organizes image features from global to local viewpoints, leading to a new objective assessment metric for retargeted images. A scale‐space matching method is designed to facilitate extraction of global geometric structures from retargeted images. By traversing the scale space from coarse to fine levels, local pixel correspondence is also established. The objective assessment metric is then based on both global geometric structures and local pixel correspondence. To evaluate color images, CIE L*a*b* color space is utilized. Experimental results are obtained to measure the performance of objective assessments with the proposed metric. The results show good consistency between the proposed objective metric and subjective assessment by human observers.

A survey on CAD methods in 3D garment design

With the advance in virtual reality applications, garment industry has strived for new developments. This paper reviews state-of-the-art CAD methods in 3D garment design. A large range of techniques are selected and organized into several key modules which form the core of a 3D garment design technology platform. In each module, basic techniques are presented first. Then advanced developments are systematically discussed and commented. The selected key modules - digital human modeling, 3D garment design and modification, numerical integration of draping, 2D pattern generation, geometric details modeling, parallel computation and GPU acceleration - are discussed in turn. Major challenges and solutions that have been addressed over the years are discussed. Finally, some of the ensuing challenges in 3D garment CAD technologies are outlined.

Construction of Iso-Contours, Bisectors, and Voronoi Diagrams on Triangulated Surfaces

In the research of computer vision and machine perception, 3D objects are usually represented by 2-manifold triangular meshes M. In this paper, we present practical and efficient algorithms to construct iso-contours, bisectors, and Voronoi diagrams of point sites on M, based on an exact geodesic metric. Compared to euclidean metric spaces, the Voronoi diagrams on M exhibit many special properties that fail all of the existing euclidean Voronoi algorithms. To provide practical algorithms for constructing geodesic-metric-based Voronoi diagrams on M, this paper studies the analytic structure of iso-contours, bisectors, and Voronoi diagrams on M. After a necessary preprocessing of model M, practical algorithms are proposed for quickly obtaining full information about iso--contours, bisectors, and Voronoi diagrams on M. The complexity of the construction algorithms is also analyzed. Finally, three interesting applications-surface sampling and reconstruction, 3D skeleton extraction, and point pattern analysis-are presented that show the potential power of the proposed algorithms in pattern analysis.

A Main Directional Mean Optical Flow Feature for Spontaneous Micro-Expression Recognition

Micro-expressions are brief facial movements characterized by short duration, involuntariness and low intensity. Recognition of spontaneous facial micro-expressions is a great challenge. In this paper, we propose a simple yet effective Main Directional Mean Optical-flow (MDMO) feature for micro-expression recognition. We apply a robust optical flow method on micro-expression video clips and partition the facial area into regions of interest (ROIs) based partially on action units. The MDMO is a ROI-based, normalized statistic feature that considers both local statistic motion information and its spatial location. One of the significant characteristics of MDMO is that its feature dimension is small. The length of a MDMO feature vector is 36 × 2 = 72, where 36 is the number of ROIs. Furthermore, to reduce the influence of noise due to head movements, we propose an optical-flow-driven method to align all frames of a micro-expression video clip. Finally, a SVM classifier with the proposed MDMO feature is adopted for micro-expression recognition. Experimental results on three spontaneous micro-expression databases, namely SMIC, CASME and CASME II, show that the MDMO can achieve better performance than two state-of-the-art baseline features, i.e., LBP-TOP and HOOF.

A computational cognition model of perception,memory,and judgment

The mechanism of human cognition and its computability provide an important theoretical foundation to intelligent computation of visual media. This paper focuses on the intelligent processing of massive data of visual media and its corresponding processes of perception, memory, and judgment in cognition. In particular, both the human cognitive mechanism and cognitive computability of visual media are investigated in this paper at the following three levels: neurophysiology, cognitive psychology, and computational modeling. A computational cognition model of Perception, Memory, and Judgment (PMJ model for short) is proposed, which consists of three stages and three pathways by integrating the cognitive mechanism and computability aspects in a unified framework. Finally, this paper illustrates the applications of the proposed PMJ model in five visual media research areas. As demonstrated by these applications, the PMJ model sheds some light on the intelligent processing of visual media, and it would be innovative for researchers to apply human cognitive mechanism to computer science.

Fast Wavefront Propagation (FWP) for Computing Exact Geodesic Distances on Meshes

Computing geodesic distances on triangle meshes is a fundamental problem in computational geometry and computer graphics. To date, two notable classes of algorithms, the Mitchell-Mount-Papadimitriou (MMP) algorithm and the Chen-Han (CH) algorithm, have been proposed. Although these algorithms can compute exact geodesic distances if numerical computation is exact, they are computationally expensive, which diminishes their usefulness for large-scale models and/or time-critical applications. In this paper, we propose the fast wavefront propagation (FWP) framework for improving the performance of both the MMP and CH algorithms. Unlike the original algorithms that propagate only a single window (a data structure locally encodes geodesic information) at each iteration, our method organizes windows with a bucket data structure so that it can process a large number of windows simultaneously without compromising wavefront quality. Thanks to its macro nature, the FWP method is less sensitive to mesh triangulation than the MMP and CH algorithms. We evaluate our FWP-based MMP and CH algorithms on a wide range of large-scale real-world models. Computational results show that our method can improve the speed by a factor of 3-10.

For micro-expression recognition: Database and suggestions

Micro-expression is gaining more attention in both the scientific field and the mass media. It represents genuine emotions that people try to conceal, thus making it a promising cue for lie detection. Since micro-expressions are considered almost imperceptible to naked eyes, researchers have sought to automatically detect and recognize these fleeting facial expressions to help people make use of such deception cues. However, the lack of well-established micro-expression databases might be the biggest obstacle. Although several databases have been developed, there may exist some problems either in the approach of eliciting micro-expression or the labeling. We built a spontaneous micro-expression database with rigorous frame spotting, AU coding and micro-expression labeling. This paper introduces how the micro-expressions were elicited in a laboratory situation and how the database was built with the guide of psychology. In addition, this paper proposes issues that may help researchers effectively use micro-expression databases and improve micro-expression recognition

EasyToy: Plush Toy Design Using Editable Sketching Curves

EasyToy is an industrial plush toy design system for novices. Editable sketching curves combine the advantages of free-form strokes and the controllability of B-spline curves. Users can continuously edit each curve to refine designs. EasyToy provides a small set of simple tools with which users can easily construct sophisticated toy models comparable to those that professional systems produce.EasyToy is an industrial plush toy design system for novices. Editable sketching curves combine the advantages of free-form strokes and the controllability of B-spline curves. Users can continuously edit each curve to refine designs. EasyToy provides a small set of simple tools with which users can easily construct sophisticated toy models comparable to those that professional systems produce.

Handling degenerate cases in exact geodesic computation on triangle meshes

The computation of exact geodesics on triangle meshes is a widely used operation in computer-aided design and computer graphics. Practical algorithms for computing such exact geodesics have been recently proposed by Surazhsky et al. [5]. By applying these geometric algorithms to real-world data, degenerate cases frequently appear. In this paper we classify and enumerate all the degenerate cases in a systematic way. Based on the classification, we present solutions to handle all the degenerate cases consistently and correctly. The common users may find the present techniques useful when they implement a robust code of computing exact geodesic paths on meshes.

A Semantic Feature Model in Concurrent Engineering

Concurrent engineering (CE) is a methodology applied to product lifecycle development so that high quality, well designed products can be provided at lower prices and in less time. Many research works have been proposed for efficiently modeling of different domains in CE. However, an integration of these works with consistent data flow is absent and still in great demand in industry. In this paper, we present a generic integration framework with a semantic feature model for knowledge representation and reasoning across domains in CE. An implementation of the proposed semantic feature model is presented to demonstrate its advantage in knowledge representation by feature transformation across domains in CE.