Zhang, Kang

Permanent URI for this collectionhttps://hdl.handle.net/10735.1/5321

Kang Zhang has a dual appointment in the Erik Jonsson School of Engineering and the School of Arts and Humanities, where he holds professorships in Computer Science and Arts and Technology. He serves as well as the Director of UTD's Visual Computing Lab. His research interests include:

  • Generation of abstract style of images,
  • Visualizing hierarchical structures,
  • Visualization of social networks, and
  • Information visualization.


Recent Submissions

Now showing 1 - 10 of 10
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    Interactive Influences of Color Attributes on Color Perception Bias
    (Springer Verlag, 2019-06-12) Yang, H.; Li, Y. -N; Zhang, Kang; 65983012 (Zhang, K); Zhang, Kang
    Graphic user interfaces and information visualization use color to represent qualitative or quantitative information. The interaction between adjacent colors leads to perceptual bias, known as simultaneous color contrast, and implicitly distort the understanding of visualized information presentation. To investigate the effect of simultaneous color contrast, we conduct two empirical experiments, in both theoretical and application settings, using a set of random target/proximal combinations of colors in the CIEL*a*b* color space. The perception bias of a target color, induced by its surround, is measured. Linear regression analysis indicates that both a high saturation of the proximal color and a high a*/low b* value of the target color cause a strong simultaneous color contrast (i.e., high perception bias). A moderating effect analysis indicates that a* value/b* value of the target color moderates the influence of the saturation of the proximal color on the perception bias. For example, controlling the saturation of the proximal color, the more reddish/yellowish the target color is, the more alleviated the perceptual bias is. ©2019, Springer-Verlag GmbH Germany, part of Springer Nature.
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    Transforming Entity-Relationship Diagrams to Relational Schemas Using a Graph Grammar Formalism
    (Institute of Electrical and Electronics Engineers Inc., 2018-12) Liu, Y.; Zeng, X.; Zhang, Kang; Zou, Y.; 65983012 (Zhang, K); Zhang, Kang
    As a formal tool extended from string grammars, graph grammars provide an intuitive yet formal way to define and transform various visual languages. This paper proposes an approach to transform Entity-Relationship diagrams (E-R diagrams) to relational schemas using a graph grammar formalism. We briefly introduce the edge-based graph grammar, on which a set of productions is designed for specifying the syntax of E-R diagrams. The set of productions can be used to verify the validity of any given E-R diagram. In addition, a procedure of transforming a given E-R diagram to a relational schema is added into the parsing process. Via the graph grammar, the automatic transformation is rigorous yet concise. We finally provide an example E-R diagram for a business management system and its transformation into relational schemas to demonstrate the specification, transformation and analyzing the power of our approach. ©2018 IEEE.
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    Transformation of Portraits to Picasso’s Cubism Style
    (Springer Verlag, 2019-05-07) Lian, G.; Zhang, Kang; 65983012 (Zhang, K); Zhang, Kang
    This paper presents an approach to the transformation of portrait photographs to Picasso’s cubism style using deep learning and image processing techniques. We obtain the side-view face by rotating the face model constructed from a frontal portrait image 90⁰ and then replace the left half of the portrait by the side-view face. Our approach is applicable to online transformation of selfie photographs and potentially extendable to broader categories of images and artistic styles. ©2019, Springer-Verlag GmbH Germany, part of Springer Nature.
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    The Influence of Edge Bundling on Visual Information Search
    (Elsevier Inc., 2019-05-04) Li, Y. -N; Zhang, Kang; Hu, D. -N; Huang, M. L.; 65983012 (Zhang, K); Zhang, Kang
    Millions of nodes and edges in a node-link diagram representing the network structure of big data may clutter the space, reducing the aesthetic quality and hindering the process of information search. Edge bundling offers an approach to solve this problem. However, to what extent that edge bundling can solve the problem remains unclear. Addressing the literature in visual complexity and Gestalt law of prägnanz, we empirically examine the influence of edge bundling on users’ information search performance, i.e., the accuracy, responding time and perceptual fluency under different levels of bundling strength. The paper reports our findings with detailed discussions. © 2019 Elsevier Inc.
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    A Human-As-Sensors Approach to API Documentation Integration and its Effects on Novice Programmers
    (Institute of Electrical and Electronics Engineers Inc.) Chen, C.; Yang, Y.; Yang, L.; Zhang, Kang; 65983012 (Zhang, K); Zhang, Kang
    In recent years, there has been a great interest in integrating crowdsourced API documents that are often dispersed across multiple places. Because of the complexity of natural language, however, automatically synthesized documents often fall short on quality and completeness compared to those authored by human experts. We develop a complementary 'human-as-sensors' approach to document integration that generates API FAQs based on users' help-seeking behavior and history. We investigated the benefits and limitations of this approach in the context of programming education. This paper describes a prototype system called COFAQ and a controlled experiment with 18 novice programmers. The study confirms that the generated FAQs effectively fosters knowledge transfer between the programmers and significantly reduce the need for repeated search. It also discovers several difficulties novice programmers encountered when seeking API help as well as the strategies they used to seek and utilize API knowledge. © 2019 IEEE.
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    Visualizing Large Graphs by Layering and Bundling Graph Edges
    (Springer Verlag) Cai, Z.; Zhang, Kang; Hu, D. -N; 65983012 (Zhang, K); Zhang, Kang
    Edge bundling has been widely used to reduce visual clutter and reveal high-level edge patterns for large graphs. Due to strong edge attraction, bundled results often show unnecessary curvature and tangling at bundle intersections. Inappropriate bundling may fail to reveal true data patterns and even mislead users. This paper presents a parameterizable 6-step edge bundling approach called LEB that reveals the patterns of the input graph, with distinguishable and traceable bundles. The bundling results by LEB are also adjustable by tuning a small number of parameters. We have conducted a user experiment to test and compare LEB with previous approaches. The experiment on three datasets (including two common ones) demonstrates LEB’s superiority over previous approaches in visualizing data patterns. Our implementation with reusable computation also delivers an execution speed fast enough for real-time interaction and animation. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.
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    Visualvital: An Observation Model for Multiple Sections of Scenes
    (Institute of Electrical and Electronics Engineers Inc.) Duan, Jun; Zhang, Kang; Hamlen, Kevin W.; 50151836493420401232 (Hamlen, KW); Duan, Jun; Zhang, Kang; Hamlen, Kevin
    A computational methodology for reorienting, repositioning, and merging camera positions within a region under surveillance is proposed, so as to optimally cover all features of interest without overburdening human or machine analysts with an overabundance of video information. This streamlines many video monitoring applications, such as vehicular traffic and security camera monitoring, which are often hampered by the difficulty of manually identifying the few specific locations (for tracks) or frames (for videos) relevant to a particular inquiry from a vast sea of hundreds or thousands of hours of video. VisualVital ameliorates this problem by considering geographic information to select ideal locations and orientations of camera positions to fully cover the span without losing key visual details. Given a target quantity of cameras, it merges relatively unimportant camera positions to reduce the quantity of video information that must be collected, maintained, and presented. Experiments apply the technique to paths chosen from maps of different cities around the world with various target camera quantities. The approach finds detail-optimizing positions with a time complexity of O(n log n). ©2017 IEEE.
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    Visual Exploration of 3d Geospatial Networks in a Virtual Reality Environment
    (Oxford University Press) Zhang, M. -J; Zhang, Kang; Li, J.; Li, Y. -N; 65983012 (Zhang, K); Zhang, Kang
    Classic geospatial network visualization tends to limit itself to 2D representation by organizing edges and nodes on a 2D map or the external surface of a traditional 3D globe model. Visual clutters and occlusions due to edge crossings and node-edge overlaps make efficient and effective exploration of geospatial networks a challenge. This paper proposes an interactive visualization approach for the intuitive exploration of geospatial networks inside a spherical virtual reality environment. To reduce visual clutter and reveal network patterns, we also propose a parameterized 5-step 3D edge-bundling algorithm and a set of techniques to avoid collision of network edges with the viewpoint. Our spherical interaction and 3D edge-bundling approach have been implemented in an Oculus Rift VR system. We demonstrate the usefulness of our approach with two case studies on real-world network data and usability experiments. ©2018 The British Computer Society. All rights reserved.
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    COPE: Interactive Exploration of Co-Occurrence Patterns in Spatial Time Series
    (IEEE Computer Society) Li, J.; Chen, S.; Zhang, Kang; Andrienko, G.; Andrienko, N.; 65983012 (Zhang, K); Zhang, Kang
    Spatial time series is a common type of data dealt with in many domains, such as economic statistics and environmental science. There have been many studies focusing on finding and analyzing various kinds of events in time series; the term ‘event’ refers to significant changes or occurrences of particular patterns formed by consecutive attribute values. We focus on a further step in event analysis: finding and exploring events that frequently co-occurred with a target class of similar events having occurred repeatedly over a period of time. This type of analysis can provide important clues for understanding the formation and spreading mechanisms of events and interdependencies among spatial locations. We propose a visual exploration framework COPE (Co-Occurrence Pattern Exploration), which allows users to extract events of interest from data and detect various co-occurrence patterns among them. Case studies and expert reviews were conducted to verify the effectiveness and scalability of COPE using two real-world datasets.
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    Visualized Awareness Support for Collaborative Software Development on Mobile Devices
    (World Scientific Publ Co Pte Ltd) Chen, Meng-Yao; Chen, Cong; Liu, Shu-Qing; Zhang, Kang; 0000 0001 1661 2720 (Zhang, K); 65983012 (Zhang, K.); Chen, Cong; Zhang, Kang
    To foster innovation and competition, an increasing number of software teams are becoming distributed. Such a distribution makes continuous collaboration and continuous awareness support a necessity and also a great challenge. Traditional desktop-based approaches are insufficient for the requirements of continuous awareness. In software development practice, an awareness tool on mobile devices is also desirable for team members to obtain the awareness information continuously. This paper addresses how to effectively present collaborative development activities using aesthetic visualization on mobile screens. Our approach supports multiple views suitable for software developers as well as team leaders. A baseline usability experiment and an eye-tracking experiment have evaluated the effectiveness and usability of the visualization method.

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