Sitaram Bhagavathy

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In this report, we propose a wavelet-based content descriptor with which we implement an image retrieval system. Initially, we propose the wavelet-based weighted standard deviation texture descriptor. We then show how to extend this descriptor to characterize both texture and color in images. Thus, we obtain a compact feature vector that characterizes(More)
In this paper we present a new physically motivated curve descriptor based on the solution of Helmholtz's equation. The descriptor satisfies the six principles set by MPEG-7: it has a good retrieval accuracy, it is compact, it can be applied in general contexts, it has a reasonable computational complexity , it is robust and provides an hierarchical(More)
— We propose the use of texture motifs, or characteristic spatially recurrent patterns for modeling and detecting geospatial objects. A method is proposed for learning a texture motif model from object examples and detecting objects based on the learned model. The model is learned in a two-layered framework—the first learns the constituent " texture(More)
We describe recent research into using the visual primitive of texture to analyze and manage large collections of remote sensed image and video data. Texture is regarded as the spatial dependence of pixel intensity. It is characterized by the amount of dependence at different scales and orientations, as measured with frequency-selective filters. A(More)
In this paper, we propose an affine-invariant method for describing and matching curves. This is important since affine transformations are often used to model perspective distortions. More specifically, we propose a new definition of the shape of a curve that characterizes a curve independently of the effects introduced by affine distortions. By combining(More)
We propose a canonical model for object classes in aerial images. This model is motivated by the observation that geographic regions of interest are characterized by collections of texture motifs corresponding to the geographic processes that generate them. We show that this model is effective in learning the common texture themes, or motifs, of the object(More)
Texture has been recognized as an important visual primitive in image analysis. A widely used texture descrip-tor, which is part of the MPEG-7 standard, is that computed using multiscale Gabor filters. The high dimen-sionality and computational complexity of this descrip-tor adversely affect the efficiency of content-based retrieval systems. We propose a(More)
In 3D Video (3DV) applications, a reduced number of views plus depth maps are transmitted or stored. When there is a need to render virtual views in between the actual views, the technique of depth image based rendering (DIBR) can be used to generate the intermediate views. To address the problem of noisy depth information in 3DV systems, we propose novel(More)
This paper proposes a scheme to detect and locate the players and the ball on the grass playfield in soccer videos. We put forward a shape analysis-based approach to identify the players and the ball from the roughly extracted foreground, which is obtained by a trained, color histogram-based playfield detector and connected component analysis. We employ(More)