8347342
Keyword-based document clustering
Document clustering is an aggregation of related documents to a cluster based on the similarity evaluation task between documents and the representatives of clusters. Terms and their discriminating features of terms are the clue to the clustering and the discriminating features are based on the term and document frequencies. Feature selection method on the basis of frequency statistics has a limitation to the enhancement of the clustering algorithm because it does not consider the contents of the cluster objects. In this paper, we adopt a content-based analytic approach to refine the similarity computation and propose a keyword-based clustering algorithm. Experimental results show that content-based keyword weighting outperforms frequency-based weighting method.
39878736
Unsupervised Learning of Pattern Templates from Unannotated Corpora for Proper Noun Extraction
This paper describes an approach to extracting proper nouns in the very large text corpora without using the lexicon or cue word dictionary. At first, we train the pattern for extracting the proper nouns by applying the initial proper names into the unannotated corpora that does not have any tags yet. And then we continuously apply the pattern templates into the corpora in order to extract new proper nouns until certain period.
11955356
Automatic Segmentation of Words using Syllable Bigram Statistics
We present a syllable bigram model for segmenting a Korean sentence into words and correcting word-spacing errors in the spelling checker. We evaluated the system’s performance for automatic word segmentation, word-spacing error detection, and the word-splitting problem of the character recognition system at the end of a line.
35348578
The Complex EGI: A New Representation for 3-D Pose Determination
The complex extended Gaussian image (CEGI), a 3D object representation that can be used to determine the pose of an object, is described. In this representation, the weight associated with each outward surface normal is a complex weight. The normal distance of the surface from the predefined origin is encoded as the phase of the weight, whereas the magnitude of the weight is the visible area of the surface. This approach decouples the orientation and translation determination into two distinct least-squares problems. The justification for using such a scheme is twofold: it not only allows the pose of the object to be extracted, but it also distinguishes a convex object from a nonconvex object having the same EGI representation. The CEGI scheme has the advantage of not requiring explicit spatial object-model surface correspondence in determining object orientation and translation. Experiments involving synthetic data of two polyhedral and two smooth objects are presented to illustrate the feasibility of this method. >
18320279
Stereo matching with reflections and translucency
In this paper, we address the stereo matching problem in the presence of reflections and translucency, where image formation can be modeled as the additive superposition of layers at different depth. The presence of such effects violates the Lambertian assumption underlying traditional stereo vision algorithms, making it impossible to recover component depths using direct color matching based methods. We develop several techniques to estimate both depths and colors of the component layers. Depth hypotheses are enumerated in pairs, one from each layer, in a nested plane sweep. For each pair of depth hypotheses, we compute a component-color-independent matching error per pixel, using a spatial-temporal differencing technique. We then use graph cut optimization to solve for the depths of both layers. This is followed by an iterative color update algorithm whose convergence is proven in our paper. We show convincing results of depth and color estimates for both synthetic and real image sequences.
1332259
On the Motion and Appearance of Specularities in Image Sequences
Real scenes are full of specularities (highlights and reflections), and yet most vision algorithms ignore them. In order to capture the appearance of realistic scenes, we need to model specularities as separate layers. In this paper, we study the behavior of specularities in static scenes as the camera moves, and describe their dependence on varying surface geometry, orientation, and scene point and camera locations. For a rectilinear camera motion with constant velocity, we study how the specular motion deviates from a straight trajectory (disparity deviation) and how much it violates the epipolar constraint (epipolar deviation). Surprisingly, for surfaces that are convex or not highly undulating, these deviations are usually quite small. We also study the appearance of specularities, i.e., how they interact with the body reflection, and with the usual occlusion ordering constraints applicable to diffuse opaque layers. We present a taxonomy of specularities based on their photometric properties as a guide for designing separation techniques. Finally, we propose a technique to extract specularities as a separate layer, and demonstrate it using an image sequence of a complex scene.
1671645
Domino logic synthesis minimizing crosstalk
Based on the new concept of crosstalk immunity set (CIS), procedures to minimize capacitive cross-coupling effects are developed for domino logic circuit. The nets in a crosstalk immunity set are free from crosstalk effects for any combination of input vectors. New algorithms for CIS identification and minimization are proposed to maximize the chance of crosstalk minimization in routing step. Our routing algorithm augmented with CIS information searches for optimal solution to minimize maximum crosstalk the circuit would experience. Experimental results show that the reduction of maximum crosstalk is up to 30% with CIS-augmented routing.
46490262
Crosstalk noise minimization in domino logic design
Based on the new concept of crosstalk immunity set (CIS), procedures to minimize capacitive crosscoupling effects are developed for domino logic circuit. The nets in a CIS are by definition free from capacitive crosscoupling effects in any combination of input vectors. New algorithms for CIS identification and CIS-driven phase assignment are proposed to maximize the chance of crosstalk minimization in routing step. Our routing algorithm augmented with CIS information searches for optimal solution to minimize maximum crosstalk the circuit would experience. Experimental results show that the reduction of maximum crosstalk is as much as 30% with CIS-augmented routing.