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Institution

International Institute of Information Technology, Hyderabad

EducationHyderabad, India
About: International Institute of Information Technology, Hyderabad is a education organization based out in Hyderabad, India. It is known for research contribution in the topics: Computer science & Authentication. The organization has 2048 authors who have published 3677 publications receiving 45319 citations. The organization is also known as: IIIT Hyderabad & International Institute of Information Technology (IIIT).


Papers
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Journal ArticleDOI
TL;DR: This work aims at learning semantic interaction among objects of generic shapes and sizes lying in clutter involving physical contact, and derives a sequence or order in which the objects surrounding the object of interest should be removed without causing damage to the environment.
Abstract: Robotic manipulation of objects in clutter remains a challenging problem to date. The challenge is posed by various levels of complexity involved in interaction among objects. Understanding these semantic interactions among different objects is important to manipulate in complex settings. It can play a significant role in extending the scope of manipulation to cluttered environment involving generic objects, and both direct and indirect physical contact. In our work, we aim at learning semantic interaction among objects of generic shapes and sizes lying in clutter involving physical contact. We infer three types of support relationships: "support from below", "support from side", and "containment". Subsequently, the learned semantic interaction or support relationship is used to derive a sequence or order in which the objects surrounding the object of interest should be removed without causing damage to the environment. The generated sequence is called support order. We also extend understanding of semantic interaction from single view to multiple views and predict support order in multiple views. Using multiple views addresses those cases that are not handled when using single view such as scenarios of occlusion or missing support relationships. We have created two RGBD datasets for our experiments on support order prediction in single view and multiple views respectively. The datasets contains RGB images, point clouds and depth maps of various objects used in day-to-day life present in clutter with physical contact and overlap. We captured many different cluttered settings involving different kinds of object-object interaction and successfully learned support relationship and performed Support Order Prediction in these settings.

20 citations

Journal ArticleDOI
TL;DR: In this paper, the dynamic response analysis of Talcher pond ash embankment in India, considering both full saturation and existing water table condition subjected to earthquake excitation, is presented.

20 citations

Proceedings ArticleDOI
01 Oct 2016
TL;DR: This paper proposes an algorithm to jointly infer the camera trajectory and the moving object trajectory simultaneously simultaneously, and achieves exact incremental solution by solving a full nonlinear optimization problem in real time.
Abstract: Real-time outdoor navigation in highly dynamic environments is an crucial problem. The recent literature on real-time static SLAM don't scale up to dynamic outdoor environments. Most of these methods assume moving objects as outliers or discard the information provided by them. We propose an algorithm to jointly infer the camera trajectory and the moving object trajectory simultaneously. In this paper, we perform a sparse scene flow based motion segmentation using a stereo camera. The segmented objects motion models are used for accurate localization of the camera trajectory as well as the moving objects. We exploit the relationship between moving objects for improving the accuracy of the poses. We formulate the poses as a factor graph incorporating all the constraints. We achieve exact incremental solution by solving a full nonlinear optimization problem in real time. The evaluation is performed on the challenging KITTI dataset with multiple moving cars. Our method outperforms the previous baselines in outdoor navigation.

20 citations

Journal ArticleDOI
TL;DR: This paper shows that a(F)=8 where F is the family of graphs of maximum degree 5 and gives a linear time algorithm to achieve this bound.

20 citations

Proceedings ArticleDOI
19 Apr 2015
TL;DR: This paper analyzes singing voice for the estimation of epochs by studying the characteristics of the source-filter interaction and the effect of wider range of pitch using the Zero Frequency Filtering (ZFF) method.
Abstract: Epoch is the instant of significant excitation of the vocal tract system during the production of voiced speech. Estimation of epochs or Glottal closure instants (GCIs) is a well studied topic in the speech analysis. From the recent studies on GCI detection from singing voice with state-of-art methods proposed for speech, there exist a clear gap in accuracy between speech and singing voice. This is because of source-filter interaction in singing voice compared to speech. Performance of existing algorithms deteriorates as most of the techniques depends on the ability to model the vocal tract system in order to emphasize the excitation characteristics in the residual. The objective of this paper is to analyze the singing voice for the estimation of epochs by studying the characteristics of the source-filter interaction and the effect of wider range of pitch using the Zero Frequency Filtering (ZFF) method. It is observed that high source-filter interaction can be captured in the form of the impulse-like excitation by passing the signal through three ideal digital resonators having poles at zero frequency, and the effect of wider range of pitch can be controlled by processing short segment (0.4–0.5 sec) signal.

20 citations


Authors

Showing all 2066 results

NameH-indexPapersCitations
Ravi Shankar6667219326
Joakim Nivre6129517203
Aravind K. Joshi5924916417
Ashok Kumar Das562789166
Malcolm F. White5517210762
B. Yegnanarayana5434012861
Ram Bilas Pachori481828140
C. V. Jawahar454799582
Saurabh Garg402066738
Himanshu Thapliyal362013992
Monika Sharma362384412
Ponnurangam Kumaraguru332696849
Abhijit Mitra332407795
Ramanathan Sowdhamini332564458
Helmut Schiessel321173527
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202310
202229
2021373
2020440
2019367
2018364