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Time filter

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Kolekar M.H.,Indian Institute of Technology Patna
Multimedia Tools and Applications | Year: 2011

This paper presents a probabilistic Bayesian belief network (BBN) method for automatic indexing of excitement clips of sports video sequences. The excitement clips from sports video sequences are extracted using audio features. The excitement clips are comprised of multiple subclips corresponding to the events such as replay, field-view, close-ups of players, close-ups of referees/umpires, spectators, players' gathering. The events are detected and classified using a hierarchical classification scheme. The BBN based on observed events is used to assign semantic concept-labels to the excitement clips, such as goals, saves, and card in soccer video, wicket and hit in cricket video sequences. The BBN based indexing results are compared with our previously proposed event-association based approach and found BBN is better than the event-association based approach. The proposed scheme provides a generalizable method for linking low-level video features with high-level semantic concepts. The generic nature of the proposed approach in the sports domain is validated by demonstrating SUCCESSFUL indexing of soccer and cricket video excitement clips. The proposed scheme offers a general approach to the automatic tagging of large scale multimedia content with rich semantics. The collection of labeled excitement clips provide a video summary for highlight browsing, video skimming, indexing and retrieval. © 2010 Springer Science+Business Media, LLC. Source


Bhaumik S.,Indian Institute of Technology Patna
Asian Journal of Control | Year: 2014

In this paper, an on-going work introducing square-root extension of cubature-quadrature based Kalman filter is reported. The proposed method is named square-root cubature-quadrature Kalman filter (SR-CQKF). Unlike ordinary cubature-quadrature Kalman filter (CQKF), the proposed method propagates and updates square-root of the error covariance without performing Cholesky decomposition at each step. Moreover SR-CQKF ensures positive semi-definiteness of the state covariance matrix. With the help of two examples we show the superior performance of SR-CQKF compared to EKF and square root cubature Kalman filter. © 2013 Chinese Automatic Control Society and Wiley Publishing Asia Pty Ltd. Source


Saha S.,Indian Institute of Technology Patna | Bandyopadhyay S.,Indian Statistical Institute
Applied Soft Computing Journal | Year: 2013

In this paper a new multiobjective (MO) clustering technique (GenClustMOO) is proposed which can automatically partition the data into an appropriate number of clusters. Each cluster is divided into several small hyperspherical subclusters and the centers of all these small sub-clusters are encoded in a string to represent the whole clustering. For assigning points to different clusters, these local sub-clusters are considered individually. For the purpose of objective function evaluation, these sub-clusters are merged appropriately to form a variable number of global clusters. Three objective functions, one reflecting the total compactness of the partitioning based on the Euclidean distance, the other reflecting the total symmetry of the clusters, and the last reflecting the cluster connectedness, are considered here. These are optimized simultaneously using AMOSA, a newly developed simulated annealing based multiobjective optimization method, in order to detect the appropriate number of clusters as well as the appropriate partitioning. The symmetry present in a partitioning is measured using a newly developed point symmetry based distance. Connectedness present in a partitioning is measured using the relative neighborhood graph concept. Since AMOSA, as well as any other MO optimization technique, provides a set of Pareto-optimal solutions, a new method is also developed to determine a single solution from this set. Thus the proposed GenClustMOO is able to detect the appropriate number of clusters and the appropriate partitioning from data sets having either well-separated clusters of any shape or symmetrical clusters with or without overlaps. The effectiveness of the proposed GenClustMOO in comparison with another recent multiobjective clustering technique (MOCK), a single objective genetic algorithm based automatic clustering technique (VGAPS-clustering), K-means and single linkage clustering techniques is comprehensively demonstrated for nineteen artificial and seven real-life data sets of varying complexities. In a part of the experiment the effectiveness of AMOSA as the underlying optimization technique in GenClustMOO is also demonstrated in comparison to another evolutionary MO algorithm, PESA2. © 2012 Elsevier B.V. All rights reserved. Source


Mehra I.,Indian Institute of Technology Patna | Nishchal N.K.,Indian Institute of Technology Patna
Optics Express | Year: 2014

Image fusion is a popular method which provides better quality fused image for interpreting the image data. In this paper, color image fusion using wavelet transform is applied for securing data through asymmetric encryption scheme and image hiding. The components of a color image corresponding to different wavelengths (red, green, and blue) are fused together using discrete wavelet transform for obtaining a better quality retrieved color image. The fused color components are encrypted using amplitude- and phase-truncation approach in Fresnel transform domain. Also, the individual color components are transformed into different cover images in order to result disguising information of input image to an attacker. Asymmetric keys, Fresnel propagation parameters, weighing factor, and three cover images provide enlarged key space and hence enhanced security. Computer simulation results support the idea of the proposed fused color image encryption scheme. © 2014 Optical Society of America. Source


Rajput S.K.,Indian Institute of Technology Patna | Nishchal N.K.,Indian Institute of Technology Patna
Applied Optics | Year: 2013

In this paper, an image encryption scheme based on polarized light encoding and a phase-truncation approach in the Fresnel transform domain is proposed. The phase-truncated data obtained by an asymmetric cryptosystem is encrypted and decrypted by using the concept of the Stokes-Mueller formalism. Image encryption based on polarization of light using Stokes-Mueller formalism has the main advantage over Jones vector formalism that it manipulates only intensity information, which is measurable. Thus any intensity information can be encrypted and decrypted using this scheme. The proposed method offers several advantages: (1) a lens-free setup, (2) flexibility in the encryption key design, (3) use of asymmetric keys, and (4) immunity against special attack. We present numerical simulation results for gray-scale and color images in support of the proposed security scheme. The performance measurement parameters relative error and correlation coefficient have been calculated to check the effectiveness of the scheme. © 2013 Optical Society of America. Source

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