Chuan-Kai Yang

Coexistence Proof Using Chain of Timestamps for Multiple RFID Tags

How can a RFID (Radio Frequency Identification Devices) system prove that two or more RFID tags are in the same location? Previous researchers have proposed yoking-proof and grouping-proof techniques to address this problem – and when these turned out to be vulnerable to replay attacks, a new existence-proof technique was proposed. We critique this class of existence-proofs and show it has three problems: (a) a race condition when multiple readers are present; (b) a race condition when multiple tags are present; and (c) a problem determining the number of tags. We present two new proof techniques, a secure timestamp proof (secTS-proof) and a timestamp-chaining proof (chaining-proof) that avoid replay attacks and solve problems in previously proposed techniques.

Integrated volume compression and visualization

Volumetric data sets require enormous storage capacity even at moderate resolution levels. The excessive storage demands not only stress the capacity of the underlying storage and communications systems, but also seriously limit the speed of volume rendering due to data movement and manipulation. A novel volumetric data visualization scheme is proposed and implemented in this work that renders 2D images directly from compressed 3D data sets. The novelty of this algorithm is that rendering is performed on the compressed representation of the volumetric data without pre-decompression. As a result, the overheads associated with both data movement and rendering processing are significantly reduced. The proposed algorithm generalizes previously proposed whole-volume frequency-domain rendering schemes by first dividing the 3D data set into subcubes, transforming each subcube to a frequency-domain representation, and applying the Fourier projection theorem to produce the projected 2D images according to given viewing angles. Compared to the whole-volume approach, the subcube-based scheme not only achieves higher compression efficiency by exploiting local coherency, but also improves the quality of resultant rendering images because it approximates the occlusion effect on a subcube by subcube basis.

Automatic Mood-Transferring between Color Images

This paper presents a new color-conversion method that offers users an intuitive, one-click interface for style conversion. So, rather than having to supply a reference image, users simply select a color mood with a mouse click. To address the color-transfer quality problem, we associate each color mood with a set of up to 10 images from our image database. After selecting their color mood, users choose one associated image. Our histogram matching algorithm then uses the selected image to determine the input images color distribution. We thereby achieve more accurate and justifiable color conversion results, while also preserving spatial coherence. Here, we further describe our solutions and their results and compare them to existing approaches.

Realization of Seurat’s pointillism via non-photorealistic rendering

Photorealistic rendering is one of the oldest and most important research areas in computer graphics. More recently, the concept of non-photorealistic rendering has been proposed as an alternative with important advantages for numerous application areas. The popularity of non-photorealism can be mainly attributed to its simplicity, which could potentially lead to a state of aesthetics and succinctness. Reality often presents too many details and too much complexity, thus offsetting the observation of the essence of objects, and objects’ interaction with lights. Based on a similar belief, impressionism focuses primarily on conveying the interaction of light and shadows without emphasizing the fine details of a scene. In recent years, there has been a trend towards simulating impressionism with computers. Among the various styles of impressionism, we are particularly interested in simulating the style of pointillism, especially the style presented by Georges-Pierre Seurat, deemed the founder of pointillism. The reason his style attracts us is twofold. First, the painting process of pointillism is extremely laborious, so unloading the main proportion of the manual painting task is mostly desired. Second, though several existing general-purposed algorithms may be able to approximate pointillism with point-like strokes, some delicate features frequently observed in Seurat’s paintings are still not satisfactorily reflected. To achieve simulating Seurat’s painting style, we have made careful observations of all accessible Seurat’s paintings and extracted from them some important features, such as the relatively few primitive colors, color juxtaposition, point sizes, and, in particular, the effects of complementary colors and halos. These features have been more successfully simulated and results are comparable with not only Seurat’s existing paintings, but also with previous attempted simulations.

On-the-Fly rendering of losslessly compressed irregular volume data

Very large irregular-grid data sets are represented as tetrahedral meshes and may incur significant disk I/O access overhead in the rendering process. An effective way to alleviate the disk I/O overhead associated with rendering a large tetrahedral mesh is to reduce the I/O bandwidth requirement through compression. Existing tetrahedral mesh compression algorithms focus only on compression efficiency and cannot be readily integrated into the mesh rendering process, and thus demand that a compressed tetrahedral mesh be decompressed before it can be rendered into a 2D image. This paper presents an integrated tetrahedral mesh compression and rendering algorithm called Gatun, which allows compressed tetrahedral meshes to be rendered incrementally as they are being decompressed, thus leading to an efficient irregular grid rendering pipeline. Both compression and rendering algorithms in Gatun exploit the same local connectivity information among adjacent tetrahedra, and thus can be tightly integrated into a unified implementation framework. Our tetrahedral compression algorithm is specifically designed to facilitate the integration with an irregular grid renderer without any compromise in compression efficiency. A unique performance advantage of Gatun is its ability to reduce the runtime memory footprint requirement by releasing memory allocated to tetrahedra as early as possible.

PaperVis: literature review made easy

Reviewing literatures for a certain research field is always important for academics. One could use Google‐like information seeking tools, but oftentimes he/she would end up obtaining too many possibly related papers, as well as the papers in the associated citation network. During such a process, a user may easily get lost after following a few links for searching or cross‐referencing. It is also difficult for the user to identify relevant/important papers from the resulting huge collection of papers. Our work, called PaperVis, endeavors to provide a user‐friendly interface to help users quickly grasp the intrinsic complex citation‐reference structures among a specific group of papers. We modify the existing Radial Space Filling (RSF) and Bullseye View techniques to arrange involved papers as a node‐link graph that better depicts the relationships among them while saving the screen space at the same time. PaperVis applies visual cues to present node attributes and their transitions among interactions, and it categorizes papers into semantically meaningful hierarchies to facilitate ensuing literature exploration. We conduct experiments on the InfoVis 2004 Contest Dataset to demonstrate the effectiveness of PaperVis.

Video Object Retrieval by Trajectory and Appearance

The prevalence of video recording capability, either on surveillance systems or mobile devices, has contributed to the popularity of video data. As a result, video management has become relatively more important than before and, in particular, video retrieval has been one of the main issues in this regard. Traditional video retrieval systems take texts as the inputs to look for similar information from the title, annotation or embedded textual data of a video, in a way that is very similar to the keyword search adopted by a common search engine. However, the lack of visual information specification during a search often makes the result rather inaccurate or even useless. For this reason, video retrieval systems using images or videos as the inputs have also been proposed; nevertheless, the associated ambiguity and complexity have made the implementation of such systems relatively difficult and, therefore, those systems are not as successful as desired. To address this, in this paper, we propose to perform a video retrieval of a desired object through the inputs of its trajectory and/or appearance, together with the help of a 3-D graphical user interface for more intuitive interactions, so that more satisfactory results can be achieved. We firmly believe that such a framework could serve as the foundation for behavior analysis used in many surveillance systems.

Face-off: automatic alteration of facial features

Pursuing or maintaining beautifulness nowadays has become a trend in modern society, especially among the celebrity community. In some cases, one may choose to adopt drastic procedures to alter his or her facial or body features to achieve the desired beauty, thus the blossom of industry on cosmetic plastic surgeries. In addition, people whose faces got damaged due to accidental burns or wounds may also find these surgeries necessary. However, as performing the related surgeries are still considered intrusive and costly, it is better to “preview” the result before a surgery is actually carried out. As many believe that facial appearance matters most, we have developed a system that allows a user to input a photo and changes the associated individual facial feature in an automatic and user-friendly manner. Overall speaking, our system makes contributions in the following four aspects. First, our system not only offers the previewing functionality, but also allows users to interactively fine-tune the desired results, thus making it a useful companion tool for facial cosmetic surgeries. Second, instead of exchanging the overall look of a face, as being done by some existing approaches, our system offers much finer granularity by allowing each and every facial feature to be changed individually and independently, thus achieving higher face-off flexibility. Third, while existing tools generally entail manual effort to locate or align facial features, our system, through the help of Active Shape Model or ASM for short, characterized by a scheme of automatic feature extraction, eliminates most of the needs of user assistance. Finally, for convenience, we have constructed a database of facial features to facilitate the facial feature alteration process. To justify our claims, we have rendered results and compared them with those from existing approaches to demonstrate the effectiveness of our system. We have also conducted a user study to further confirm the usefulness of such a system.

I/O-Conscious Volume Rendering

Most existing volume rendering algorithms assume that data sets are memory-resident and thus ignore the performance overhead of disk I/O. While this assumption may be true for high-performance graphics machines, it does not hold for most desktop personal workstations. To minimize the end-to-end volume rendering time, this work re-examines implementation strategies of the ray casting algorithm, taking into account both computation and I/O overheads. Specifically, we developed a data-driven execution model for ray casting that achieves the maximum overlap between rendering computation and disk I/O. Together with other performance optimizations, on a 300-MHz Pentium-II machine, without directional shading, our implementation is able to render a 128x128 greyscale image from a 128x128x128 data set with an average end-to-end delay of 1 second, which is very close to the memory-resident rendering time. With a little modification, this work can also be extended to do out-of-core visualization as well.

Zodiac: a history-based interactive video authoring system

Abstract. Easy-to-use audio/video authoring tools play a crucial role in moving multimedia software from research curiosity to mainstream applications. However, research in multimedia authoring systems has rarely been documented in the literature. This paper describes the design and implementation of an interactive video authoring system called Zodiac, which employs an innovative edit history abstraction to support several unique editing features not found in existing commercial and research video editing systems. Zodiac provides users a conceptually clean and semantically powerful branching history model of edit operations to organize the authoring process, and to navigate among versions of authored documents. In addition, by analyzing the edit history, Zodiac is able to reliably detect a composed video streams shot and scene boundaries, which facilitates interactive video browsing. Zodiac also features a video object annotation capability that allows users to associate annotations to moving objects in a video sequence. The annotations themselves could be text, image, audio, or video. Zodiac is built on top of MMFS, a file system specifically designed for interactive multimedia development environments, and implements an internal buffer manager that supports transparent lossless compression/decompression. Shot/scene detection, video object annotation, and buffer management all exploit the edit history information for performance optimization.