16964451
HISA: a query system bridging the semantic gap for large image databases
We propose a novel system called HISA for organizing very large image databases. HISA implements the first known data structure to capture both the ontological knowledge and visual features for effective and effcient retrieval of images by either keywords, image examples, or both. HISA employs automatic image annotation technique, ontology analysis and statistical analysis of domain knowledge to precompute the data structure. Using these techniques, HISA is able to bridge the gap between the image semantics and the visual features, therefore providing more user-friendly and high-performance queries. We demonstrate the novel data structure employed by HISA, the query algorithms, and the pre-computation process.
116588251
On-line evolutionary exponential family mixture
This paper deals with evolutionary clustering, which refers to the problem of clustering data with distribution drifting along time. Starting from a density estimation view to clustering problems, we propose two general on-line frameworks. In the first framework, i.e., historical data dependent (HDD), current model distribution is designed to approximate both current and historical data distributions. In the second framework, i.e., historical model dependent (HMD), current model distribution is designed to approximate both current data distribution and historical model distribution. Both frameworks are based on the general exponential family mixture (EFM) model. As a result, all conventional clustering algorithms based on EFMs can be extended to evolutionary setting under the two frameworks. Empirical results validate the two frameworks.
5747087
Efficient Processing of Warping Time Series Join of Motion Capture Data
Discovering non-trivial matching subsequences from two time series is very useful in synthesizing novel time series. This can be applied to applications such as motion synthesis where smooth and natural motion sequences are often required to be generated from existing motion sequences. We first address this problem by defining it as a problem of l-e-join over two time series. Given two time series, the goal of l-e-join is to find those non-trivial matching subsequences by detecting maximal l-connections from the e-matching matrix of the two time series. Given a querying motion sequence, the l-e-join can be applied to retrieve all connectable motion sequences from a database of motion sequences. To support efficient l-e-join of time series, we propose a two-step filter-and-refine algorithm, called Warping Time Series Join (WTSJ) algorithm. The filtering step serves to prune those sparse regions of the e-matching matrix where there are no maximal l-connections without incurring costly computation. The refinement step serves to detect closed l-connections within regions that cannot be pruned by the filtering step. To speed up the computation of e-matching matrix, we propose a block-based time series summarization method, based on which the block-wise e-matching matrix is first computed. Lots of pairwise distance computation of elements can then be avoided by applying the filtering algorithm on the block-wise e-matching matrix.Extensive experiments on l-e-join of motion capture sequences are conducted. The results confirm the efficiency and effectiveness of our proposed algorithm in processing l-e-join of motion capture time series.
8340253
UGE4B: An Universal Grid Environment for Bioinformatics Research
Recent years, grid technology has been used widely in the fields of scientific research. In this paper, we present a universal grid environment for bioinformatics research (UGE4B). Although there have been several similar projects successfully constructed in the world, we need to meet some unique requirements from bioinformatics research in China. UGE4B consists of 6 components, including portal, task management, data management, information server, security and computing node. As a national-wide bioinformatics research platform, UGE4B is built through interconnecting multiple sub grids provided by each bioinformatics institutes. Besides provides a universal portal to end users for bioinformatics computing and data accessing, UGE4B also supported some special bioinformatics applications
8051159
A Web-based Framework For On-line Collaborative Learning
This paper presents a framework for design of online courses and collaborative learning based on Web technologies. It provides the following features: construction of structured learning materials in a distributed environment; personalization of course contents in the run-time that adapts to the progress of individual students; it can supply relevant Web resources to the students by analyzing the learning history dynamically; students in a group could exchange their learning experiences and discover relevant knowledge via the communication channels provided by the framework. The proposed techniques could be deployed to a variety of online computer-assisted modules to improve the effectiveness of Web-based e-learning
1107258
Improving image clustering: An unsupervised feature weight learning framework
We address the problem of feature weight learning for image clustering. In practice, before clustering data, we generally normalize all data features between 0 and 1, because we cannot determine which features are more important. In this paper, we provide a feature weight learning framework for clustering which can obtain the feature weights and cluster labels simultaneously. An alternative optimization algorithm is adopted to solve this problem. Empirical studies on the toy data and real image data demonstrate our algorithm's effectiveness in improving the clustering performance.
29357540
Multi-feature Fusion Method of Driver Face Location Based on Area Coincidence Degree and Prior Knowledge
Speedy and reliable face location is a key for monitoring driver fatigue driving condition using machine vision methods. According to the disadvantage of face location methods based on single feature in accuracy and reliability at present, first, an improved face location method based on Haar-like feature and Adaboost is used to detect the possibly existing face region in the whole image, then the detected region is extended properly and a face location method based on skin color feature in normalized rgb and HSV color spaces is used to locate the face again in the extended area, finally, fusion location of driver face region is achieved by the defined area coincidence degree and prior knowledge of human face. Experiments carried out in various road environments demonstrate the validity of the fusion method proposed.
7031383
Image retrieval based on Sugeno fuzzy integral
In this paper, we propose a fuzzy similarity measure based on the Sugeno fuzzy integral and apply it to the content-based image retrieval. Fuzzy measure is used to formulate the subjective feedback information. Experimental results show that the proposed method can improve the efficiency and reliability of image retrieval system. Our method of formulating the subjective feedback information performs better than the weighted average operator (WAO) and a Choquet-integral-based similarity measure.
7606399
A fuzzy image metric with application to fractal coding
Image quality assessment is an important issue addressed in various image processing applications such as image/video compression and image reconstruction. The peak signal-to-noise ratio (PSNR) with the L(2)-metric is commonly used in objective image quality assessment. However, the measure does not agree very well with the human visual perception in many cases. A fuzzy image metric (FIM) is defined based on Sugeno's (1977) fuzzy integral. This new objective image metric, which is to some extent a proper evaluation from the viewpoint of the judgment procedure, is closely approximates the subjective mean opinion score (MOS) with a correlation coefficient of about 0.94, as compared to 0.82 obtained using the PSNR. Compared to the L(2)-metric, we demonstrate that a better performance can be achieved in fractal coding by using the proposed FIM.
6110208
Nanophotonics — Quantum dots, photonic crystals, and optical silicon circuits: An excursion into the optical behavior of very small things
This paper covers four specific areas — diverse in their scope and approach — of nanophotonics research at Bell Labs, ranging from nanosized light emitters to passive and active optical circuits fabricated or actuated with nanometer precision. Our first example involves the dynamics of carriers confined in quantum dots fabricated via self-assembly on semiconducting substrates; we show that the evolution of carrier populations is a result of the interplay of interactions between photons, phonons, electrons, and holes. A second example involves a nanosize light-emitting quantum dot system that is fabricated by embedding passivated spherical semiconducting quantum dots in a polymer matrix; the fabrication steps and subsequent optical measurements, including the observation of net optical gain in this system, are described. In the area of passive and active optical circuits, we report on efforts to optimize the transmission efficiencies of photonic crystal circuit-building elements (e.g., waveguide bends and waveguide tapers in passive two-dimensional photonic crystal circuits). Finally, we describe active optical silicon circuits fabricated on a silicon-on-insulator platform; these devices comprise waveguide interferometers and electrostatically actuated piston micromirrors, and they require nanometer-size displacements to function as optical switches with inherently low power consumption.
31400188
Image Recovery from Broken Image Streams
This paper presents an approach for image recovery from broken image streams based on an image continuity model. The information to be recovered includes the header of an image (width, height, color space etc.) and the data stream which might have been partially damaged. We begin our discussion on common image formats and necessary information for the image recovery. We then define several measures on image contents to facilitate the image recovery. Using these measures, an effective recovery algorithm is proposed. Experimental results show that the algorithm can successfully recover images of different formats, even multi-frame images from broken image streams in most cases.