International Institute of Information Technology, Hyderabad

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).

Robust homography-based control for camera positioning in piecewise planar environments

Abstract: This paper presents a vision-based control for positioning a camera with respect to an unknown piecewise planar object. We introduce a novel homography-based approach that integrates information from multiple homographies to reliably estimate the relative displacement of the camera. This approach is robust to image measurement errors and provides a stable estimate of the camera motion that is free from degeneracies in the task space. We also develop a new control formulation that meets the contradictory requirements of producing a decoupled camera trajectory and ensuring object visibility by only utilizing the homography relating the two views. Experimental results validate the efficiency and robustness of our approach and demonstrate its applicability.

Developing Verb Frames for Hindi

Abstract: This paper introduces an ongoing work on developing verb frames for Hindi. Verb frames capture syntactic commonalities of semantically related verbs. The main objective of this work is to create a linguistic resource which will prove to be indispensable for various NLP applications. We also hope this resource to help us better understand Hindi verbs. We motivate the basic verb argument structure using relations as introduced by Panini. We show the methodology used in preparing these frames and the criteria followed for classifying Hindi verbs.

Identifying tandem Ankyrin repeats in protein structures

Abstract: Tandem repetition of structural motifs in proteins is frequently observed across all forms of life. Topology of repeating unit and its frequency of occurrence are associated to a wide range of structural and functional roles in diverse proteins, and defects in repeat proteins have been associated with a number of diseases. It is thus desirable to accurately identify specific repeat type and its copy number. Weak evolutionary constraints on repeat units and insertions/deletions between them make their identification difficult at the sequence level and structure based approaches are desired. The proposed graph spectral approach is based on protein structure represented as a graph for detecting one of the most frequently observed structural repeats, Ankyrin repeat. It has been shown in a large number of studies that 3-dimensional topology of a protein structure is well captured by a graph, making it possible to analyze a complex protein structure as a mathematical entity. In this study we show that eigen spectra profile of a protein structure graph exhibits a unique repetitive profile for contiguous repeating units enabling the detection of the repeat region and the repeat type. The proposed approach uses a non-redundant set of 58 Ankyrin proteins to define rules for the detection of Ankyrin repeat motifs. It is evaluated on a set of 370 proteins comprising 125 known Ankyrin proteins and remaining non-solenoid proteins and the prediction compared with UniProt annotation, sequence-based approach, RADAR, and structure-based approach, ConSole. To show the efficacy of the approach, we analyzed the complete PDB structural database and identified 641 previously unrecognized Ankyrin repeat proteins. We observe a unique eigen spectra profile for different repeat types and show that the method can be easily extended to detect other repeat types. It is implemented as a web server, AnkPred. It is freely available at ‘bioinf.iiit.ac.in/AnkPred’. AnkPred provides an elegant and computationally efficient graph-based approach for detecting Ankyrin structural repeats in proteins. By analyzing the eigen spectra of the protein structure graph and secondary structure information, characteristic features of a known repeat family are identified. This method is especially useful in correctly identifying new members of a repeat family.

Design of a secure smart card-based multi-server authentication scheme

Abstract: Traditional two party client server authentication protocol may not provide a scalable solution for present network environments where personal and ubiquitous computing technologies are involved as it is now becoming multi-server based. To achieve efficient authorized communication, multi-server based authentication protocols have been designed. The key feature of multi-server based protocols is one time registration. We study the existing multi-server based authentication protocols, and identify that many of the multi-server based authentication protocols involve control server in mutual authentication or trusted server environment is required. The involvement of central authority in mutual authentication may be a bottleneck for large network, and the servers may be semi-trusted. To erase these drawbacks, Wei etźal. recently proposed a multi-server based authentication protocol. Their protocol does not require all servers to be trusted and involvement of control server in mutual authentication. Unfortunately, we identify the security vulnerability of Wei etźal.'s scheme to insider attack and password guessing attack. Additionally, lack of pre-smart card authentication leads to denial of service attack. To enhance the security of Wei etźal.'s protocol, we propose a secure biometric-based authentication scheme for multi-server environment using smart card. We simulate the proposed protocol for the formal security verification using the widely accepted AVISPA (Automated Validation of Internet Security Protocols and Applications) tool to show that our scheme is secure against active and passive attacks. In addition, we prove that our proposed scheme provides mutual authentication using the widely-accepted Burrows-Abadi-Needham (BAN) logic and is also secured against various well known attacks. In addition, our scheme is efficient in terms of computational and communication overheads as compared to Wei etźal.'s scheme and other existing related schemes.

Quo Vadis, Skeleton Action Recognition ?

Abstract: In this paper, we study current and upcoming frontiers across the landscape of skeleton-based human action recognition. To begin with, we benchmark state-of-the-art models on the NTU-120 dataset and provide multi-layered assessment of the results. To examine skeleton action recognition 'in the wild', we introduce Skeletics-152, a curated and 3-D pose-annotated subset of RGB videos sourced from Kinetics-700, a large-scale action dataset. The results from benchmarking the top performers of NTU-120 on Skeletics-152 reveal the challenges and domain gap induced by actions 'in the wild'. We extend our study to include out-of-context actions by introducing Skeleton-Mimetics, a dataset derived from the recently introduced Mimetics dataset. Finally, as a new frontier for action recognition, we introduce Metaphorics, a dataset with caption-style annotated YouTube videos of the popular social game Dumb Charades and interpretative dance performances. Overall, our work characterizes the strengths and limitations of existing approaches and datasets. It also provides an assessment of top-performing approaches across a spectrum of activity settings and via the introduced datasets, proposes new frontiers for human action recognition.