Department of Computer Science & Engineering

&ldquo;IIT Jodhpur is committed to impart quality education to facilitate the creation of qualified, competent and responsible human resources to meet the emerging technological challenges of the world. It is working towards creating an equitable learning platform that is positive, accessible and effective in the face of the modern societal and scientific advancements.

Flexibility in curriculum, in all its academic programs, encompassing elements of teaching, research, creativity, innovation and entrepreneurship is the most unique feature of IIT Jodhpur. The Department of Science and Technology (DST), under the National Mission on Cyber Physical Systems, has identified IIT Jodhpur as a Technology &amp; Innovation Hub in the area of Augmented Reality and Virtual Reality. The institute has also been nominated as the coordinator for the Jodhpur City and Knowledge Cluster by the Office of Principal Scientific Adviser, Government of India.

The sprawling 852-acre IIT Jodhpur campus is a majestic tribute to the deep-rooted diverse cultural heritage of the region. The campus is an architectural masterpiece, which is slated to become an international exemplar of sustainability with net-zero energy, and advanced water and waste management strategies.&rdquo;

IIT Jodhpur

Sketch recognition is one of the most challenging applications of face recognition. Due to the incorrectness of features in the witness description, standard face recognition algorithms are generally not applicable to matching sketches with digital face images. This research designs a patch based face recognition algorithm that generates patches around fiducial features and extracts local information from these patches using Daisy descriptor. The information extracted from these patches are then efficiently matched using GentleBoostKO algorithm. The experiments performed on the PRIP composite face image database show that the proposed algorithm yields promising results and outperforms existing state-of-the-art algorithms and a commercial system. © 2013 IEEE.

World University root node

2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings

Boosting local descriptors for matching composite and digital face images

Matching sketches with digital face images is one of the highly sought face recognition applications. An important aspect, though less explored till now, is matching age separated sketches with digital face images. Several law enforcement agencies are progressively using composite sketches for apprehending individuals. This research proposes an algorithm for matching composite sketches with digital face images across different age. It extracts discriminative shape, orientation, and texture features from local regions of a face using image moments and histogram of oriented gradients. The complementary information from these two features is further combined at match score level for efficiently matching composite sketches with digital face images across different age. To study the effects of age variations, this research also presents a composite sketch database with age separated sketches and digital face images. The results on a large gallery experiment suggest that the proposed algorithm efficiently encodes discriminative information from local facial regions useful for matching composite sketches with age separated digital face images. © 2013 IEEE.

IEEE 6th International Conference on Biometrics: Theory, Applications and Systems, BTAS 2013

Matching age separated composite sketches and digital face images

With the prevalent utilization of citizen databases, an individual has to prove his/her identity for accessing several services such as banking, health care, and social welfare benefits. These databases are now increasingly using demographic and biometric information to uniquely identify the individuals. It protects the core identity of citizens and facilitates them to receive the entitled benefits and rights. It is therefore important that every citizen should enroll only once in the database and be assigned only one unique identifier. De-duplication process prevents an individual from enrolling multiple times in the database. It is essential to understand the importance of constituent information (demographic and biometric) in the de-duplication process. Using a large database, this research attempts to fill the gap in existing literature by analyzing the performance of demographic and biometric information for de-duplication. The study presents the results when demographic and biometric information are individually processed and complementary information from the two modalities are combined at match score level for de-duplication under different operating scenarios. © 2013 IEEE.

IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

Can combining demographics and biometrics improve de-duplication performance?

Simultaneous measurement of multi-dimensional deformations can be done in digital holographic Moiré by illuminating the object with multiple beams from different angles and recording the interference pattern due to multiple beams. This technique involves reliable estimation of resultant multiple phase maps from a one record of the reconstructed interference moiré field. In this paper, we introduce a novel method, based on Unscented Kalman Filter (UKF), for the estimation of multiple phase maps from a complex multi-component signal encountered in digital holographic moiré. The State space model used in this method is determined by Taylor series expansion of phase component as process model and polar to Cartesian conversion as measurement model. © 2013 IEEE.

2013 4th National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics, NCVPRIPG 2013

UKF based multi-component phase estimation in digital holographic Moiré

This paper analyses an image watermarking scheme based on Support Vector Regression (SVR) proposed by R. Shen et al. We describe various attacks against this scheme and show that watermark tampering can be done even when one does not know the secret key used to embed the watermark. Next we discuss methods to extract the keys used in the scheme under various usage scenarios. Our results show that Shen et al.'s scheme is not secure. © 2013 IEEE.

Proceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013

Cryptanalysis of a digital watermarking scheme based on support vector regression

This paper suggests an approach for formalizing Tuple Space based Mobile Middleware (TSMM) that contains a fully-decoupled reactive tuple space model as coordination medium. Formalization of TSMM is carried out using Mobile UNITY. © 2013 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering.

Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering

Formalization of a fully-decoupled reactive tuple space model for mobile middleware

Data gathering or convergecast is one of the most popular applications of road side sensor network where the data sensed from the road are accumulated in the road side gateways or sinks for traffic monitoring purpose. The required delay sensitivity and reliability of the application as well as the scarcity of sensor resources make the task challenging. In this paper, a novel tree based data gathering scheme has been proposed exploiting the strip like structure of the road network. Sensor nodes are distributed in several virtual blocks along the road and a convergecast tree is constructed selecting one active node from each block. Implementation of efficient scheduling assures both the coverage and critical power savings of sensor nodes. The network connectivity is guaranteed throughout by the proposed tree maintenance module that handles the sensor node joining and leaving events. Simulation results show that the tree maintenance overhead in terms of both delay and control message communication is nominal. © 2013 IEEE.

Proceedings - International Conference on Advanced Information Networking and Applications, AINA

Energy-efficient data gathering for road-side sensor networks ensuring reliability and fault-tolerance

ACM International Conference Proceeding Series

ACM International Conference Proceeding Series: Preface

We propose a framework for retrieving metric information for repeated objects from single perspective image. Relative affine structure, which is an invariant, is directly proportional to the Euclidean distance of a three dimensional point from a reference plane. The proposed method is based on this fundamental concept. The first object undergoes 4 × 4 transformation and results in a repeated object. We represent this transformation in terms of three relative affine structures along X, Y and Z axes. Additionally, we propose the possible extension of this framework for motion analysis - structure from motion and motion segmentation. © 2013 IEEE.

Complete visual metrology using relative affine structure

This paper presents a novel parameterized variety based view synthesis scheme for 3DTV and multi-view systems. We have generalized the parameterized image variety approach to image based rendering proposed in [1] to handle full perspective cameras. An algebraic geometry framework is proposed for the parameterization of the variety associated with full perspective images, by image positions of three reference scene points. A complete parameterization of the 3D scene is constructed. This allows to generate realistic novel views from arbitrary viewpoints without explicit 3D reconstruction, taking few multi-view images as input from uncalibrated cameras. Another contribution of this paper is to provide a generalised and flexible architecture based on this variety model for multi-view 3DTV. The novelty of the architecture lies in merging this variety based approach with standard depth image based view synthesis pipeline, without explicitly obtaining sparse or dense 3D points. This integrated framework subsequently overcomes the problems associated with existing depth based representations. The key aspects of this joint framework are: 1) Synthesis of artifacts free novel views from arbitrary camera positions for wide angle viewing. 2) Generation of signal representation compatible with standard multi-view systems. 3) Extraction of reliable view dependent depth maps from arbitrary virtual viewpoints without recovering exact 3D points. 4) Intuitive interface for virtual view specification based on scene content. Experimental results on standard multi-view sequences are presented to demonstrate the effectiveness of the proposed scheme. © 2013 Springer-Verlag.