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

The paper proposes a novel multi-modal document image retrieval framework by exploiting the information of text and graphics regions. The framework applies multiple kernel learning based hashing formulation for generation of composite document indexes using different modalities. The existing multimedia management methods for imaged text documents have not addressed the requirement of old and degraded documents. In the subsequent contribution, we propose novel multi-modal document indexing framework for retrieval of old and degraded text documents by combining OCR'ed text and image based representation using learning. The evaluation of proposed concepts is demonstrated on sampled magazine cover pages, and documents of Devanagari script. © 2013 IEEE.

World University root node

Proceedings of the International Conference on Document Analysis and Recognition, ICDAR

Multi-modal information integration for document retrieval

In this paper, we are presenting a framework for 'User's Personalized Workspace' by augmenting the physical paper and digital document. The paper based interactions are seamlessly integrated with digital document based interactions for reading as a activity. For instance when user is involved in reading activity, writing becomes complimentary. In a academic system, paper based presentation mode has facilitated such exercises. Despite rendering the annotation on digital document and store it onto the database, the content of the paper encircled or underlined is used to hyperlink the document. Synchronizing a physical paper and those of digital version in seamless fashion from a user's perspective is the main objective of this work. We have also compared the existing systems which focus on one activity or the other in our proposed system. © 2013 IEEE.

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

Augmented paper system: A framework for User's Personalized Workspace

Large space with many cameras require huge storage and computational power to process these data for surveillance applications. In this paper we propose a distributed camera and processing based face detection and recognition system which can generate information for finding spatiotemporal movement pattern of individuals over a large monitored space. The system is built upon Hadoop Distributed File System using map reduce programming model. A novel key generation scheme using distance based hashing technique has been used for distribution of the face matching task. Experimental results have established effectiveness of the technique. © 2013 IEEE.

Monitoring a large surveillance space through distributed face matching

In this paper, we propose an archiving scheme for heritage mural paintings. The mural paintings typically depict stories from folk-lore, mythology and history. These narratives provide content-based correlations between different pieces of art. Our e-heritage scheme for archiving the mural paintings is based on an ontology which captures the background knowledge of these narratives. Media features and patterns derived from the mural content are used to enrich the ontology with multimedia data. We have used the multimedia web ontology language as our ontology representation scheme, as it allows perceptual modelling of domain concepts in terms of their media properties, as well as reasoning with uncertainties. Besides the mural content and its knowledge, the ontology also helps encode other aspects of the mural paintings like their painting style, color, physical location, time-period, etc., which are important parameters of their preservation. We propose a framework to provide cross-modal semantic linkage between semantically annotated content of a repository of Indian mural paintings, and a collection of labelled text documents of their narratives. This framework, based on a multimedia ontology of the domain, helps preserve the cultural heritage encoded in these artefacts. © 2013 Springer-Verlag.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Archiving mural paintings using an ontology based approach

Clarity of a latent impression is defined as the discern-ability of fingerprint features while quality is defined as the amount (number) of features contributing towards matching. Automated estimation of clarity and quality at local regions in a latent fingerprint is a research challenge and has received limited attention in the literature. Local clarity and quality helps in better extraction of features and assessing the confidence of matches. The research focuses on (i) developing an automated local clarity estimation algorithm, (ii) developing an automated local quality estimation algorithm based on clarity, and (iii) understanding the correlation between clarity and quality in latent fingerprints. Local clarity assessment is performed using a 2-D linear symmetric structure tensor. The goodness of orientation field is proposed to estimate the local quality of a latent fingerprint. Experiments on the NIST SD-27 database show that incorporating local clarity information in the quality assessment improves the performance of the matching system. © 2013 IEEE.

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

Automated clarity and quality assessment for latent fingerprints

The phenomenon of 'aging' in humans leads to significant variations in facial features. Various factors such as bone growth, ethnicity and dietary habits influence the facial aging pattern. This increases the difficulty in performing automated face recognition. In this paper, we propose an algorithm that improves the performance of face recognition by applying the bacteria foraging fusion algorithm. The proposed algorithm mitigates the effect of facial changes caused due to aging by combining the LBP features of global and local facial regions at match score level, by means of the bacteria foraging fusion algorithm. Experimental results are presented using the FG-Net and IIITDelhi face aging databases. The IIITDelhi database, which has been collected by the authors, consists of over 2600 age-separated labeled face images of 102 individuals. To account for real life and natural conditions, images include changes in the face due to illumination, pose, and presence of accessories such as eyeglasses. The results demonstrate that the proposed approach outperforms traditional fusion schemes, existing algorithms and a commercial system. © 2013 IEEE.

IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

Bacteria foraging fusion for face recognition across age progression

Study of structural, optical and photoconductivity in ZnO nanoparticles codoped with Mg and Cd

Geographic Perimeter Stateless Routing (GPSR) use local information to forward packets greedily. Nodes need to keep only this information, hence called as stateless. When not possible the algorithm and Greedy forwarding recovers to this scenario by switching to face routing, which is further based on the right-hand rule in the planarized node graph, in order to route around the void. The Gabriel Graph(GG) and the Relative Neighbourhood Graph (RNG) are the two graphs used for the planarization, but results in graph partitioning. In this work, we propose an improvised RNG-GG algorithm which makes sure to avoid the partitioning of the underlying connected graph and the cross-link, which remain in the node connectivity graph. We have given simulation results for the performance analysis of our proposed protocol compared to the competitive schemes and found improvement in terms of an increased packet delivery success rate, reducing routing protocol overhead and increased the path length. © 2013 IEEE.

2013 IEEE Recent Advances in Intelligent Computational Systems, RAICS 2013

Improvised geographic scheme for greedy perimeter stateless routing

The efficiency and reliability of convergecast in sensor network depends on the correct and efficient accumulation of data to the sink. A tree, rooted at the sink, that utilizes sensor resources properly is an ideal topology for data gathering. Resource constrained sensor nodes are highly prone to sudden crash. So the application demands a quick and efficient repairing of the tree when a node dies. The proposed scheme builds a data gathering tree rooted at the sink. The tree eventually becomes a Breadth First Search (BFS) tree where each node maintains the shortest hop-count to the root to reduce the routing delay. Each node collects some extra neighborhood information during the tree construction. Thus a little pre-processing at each node helps in taking prompt actions to repair the tree through local adjustment if any arbitrary single or multiple nodes fail in future. On failure of a node, each affected node in its vicinity fixes the parent through a pair of control message transmissions. Simulation results show that the repairing delay is significantly less in average and the convergecast messages are delivered with minimum data loss and no redundancy even in presence of node crash. © 2013 Elsevier B.V. All rights reserved.

Ad Hoc Networks

Convergecast tree management from arbitrary node failure in sensor network

IEEE 802.11s provides Hybrid Wireless Mesh Protocol (HWMP) to find out the forwarding path in a mesh network based on mesh peering and MAC layer scheduling information. However, both proactive and reactive modes of HWMP perform poorly for multi-radio mesh network because of inefficient radio selection, time-varying channel conditions and interference among the radios. This paper proposes an improved opportunistic path selection protocol over HWMP for multi-radio support that goes beyond the traditional routing mechanisms, operates either in proactive, reactive or hybrid mode. The efficiency of the proposed scheme is analyzed using simulation results. © 2013 IEEE.