In this paper, we propose a novel cascading approach, by cascading the feature selection method using mutual correlation with this symbolic approach. In the symbolic approach, the new dimensionality reduction method through transformation of features into symbolic data using the property of collinearity and variance based cumulative sum of features is used. The feature values are transformed in...

In this paper, we propose a novel cascading approach, by cascading the feature selection method using mutual correlation with this symbolic approach. In the symbolic approach, the new dimensionality reduction method through transformation of features into symbolic data using the property of collinearity and variance based cumulative sum of features is used. The feature values are transformed in...

In this paper, we propose a novel cascading approach, by cascading the feature selection method using mutual correlation with this symbolic approach. In the symbolic approach, the new dimensionality reduction method through transformation of features into symbolic data using the property of collinearity and variance based cumulative sum of features is used. The feature values are transformed in...

In this paper, we propose a novel cascading approach, by cascading the feature selection method using mutual correlation with this symbolic approach. In the symbolic approach, the new dimensionality reduction method through transformation of features into symbolic data using the property of collinearity and variance based cumulative sum of features is used. The feature values are transformed in...

This article proposes a global approach to the rectification of sport sequences, to estimate the mapping from the video images to the terrain in the ground plane without using position sensors on the TV camera. Our strategy relies on three complementary techniques: (1) initial homography estimation using line-feature matching, (2) homography estimation with line-feature tracking, and (3) increm...

In this paper, we propose a novel cascading approach, by cascading the feature selection method using mutual correlation with this symbolic approach. In the symbolic approach, the new dimensionality reduction method through transformation of features into symbolic data using the property of collinearity and variance based cumulative sum of features is used. The feature values are transformed in...

In this paper, two novel features, Line Spectrum Center Range and Line Spectrum Flux, both derived from Line Spectrum Frequencies, are proposed to detect the presence of speech in various acoustic environments. Evaluation results using Fischer Discriminant Analysis and Scatter Matrices indicated that the new features excel the state-of-theart features. An environmental robust hybrid feature set...

Variability in a Software Product Line (SPL) is expressed in terms of a feature model. As software development efforts involve increasingly larger feature models, scalable techniques are required to manage their complexity. Furthermore, as many stakeholders have a vested interest in different aspects of a feature model, modularity techniques are required to independently expresses their views o...

Sharp features in manufactured and designed objects require particular attention when reconstructing surfaces from unorganized scan point sets using moving least squares (MLS) fitting. It’s an inherent property of MLS fitting that sharp features are smoothed out. Instead of searching for appropriate new fitting functions our approach computes a modified local point neighborhood so that a standa...