Clustering is the unsupervised classification of patterns (observations, data items, or feature vectors) into groups (clusters). The clustering problem has been addressed in many contexts and by researchers in many disciplines; this reflects its broad appeal and usefulness as one of the steps in exploratory data analysis. However, clustering is a difficult problem combinatorially, and differences in assumptions and contexts in different communities has made the transfer of useful generic concepts and methodologies slow to occur. This paper presents an overview of pattern clustering methods from a statistical pattern recognition perspective, with a goal of providing useful advice and references to fundamental concepts accessible to the broad community of clustering practitioners. We present a taxonomy of clustering techniques, and identify cross-cutting themes and recent advances. We also describe some important applications of clustering algorithms such as image segmentation, object recognition, and information retrieval.

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Data clustering: a review

“Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks”の学習報告

From the Publisher: 
The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

Handwriting has continued to persist as a means of communication and recording information in day-to-day life even with the introduction of new technologies. Given its ubiquity in human transactions, machine recognition of handwriting has practical significance, as in reading handwritten notes in a PDA, in postal addresses on envelopes, in amounts in bank checks, in handwritten fields in forms, etc. This overview describes the nature of handwritten language, how it is transduced into electronic data, and the basic concepts behind written language recognition algorithms. Both the online case (which pertains to the availability of trajectory data during writing) and the off-line case (which pertains to scanned images) are considered. Algorithms for preprocessing, character and word recognition, and performance with practical systems are indicated. Other fields of application, like signature verification, writer authentification, handwriting learning tools are also considered.

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Online and off-line handwriting recognition: a comprehensive survey

IEEE Transactions on Pattern Analysis and Machine Intelligence

This paper provides an overview of the contents of a tutorial on the subject by one of the authors at WI-2013 Conference. The domination of multimedia contents on the web in recent times has motivated research in their semantic analysis. This tutorial aims to provide a critical overview of the technology, and focuses on application of ontologies for multimedia applications. It establishes the need for a fundamentally different approach for a representation and reasoning scheme with ontologies for semantic interpretation of multimedia contents. It introduces a new ontology representation scheme that enables reasoning with uncertain media properties of concepts in a domain context and a language “Multimedia Web Ontology Language” (MOWL) to support the representation scheme. We discuss the approaches to semantic modeling and ontology learning with specific reference to the probabilistic framework of MOWL. We present a couple of illustrative application examples. Further, we discuss the issues of distributed multimedia information systems and how the new ontology representation scheme can create semantic interoperability across heterogeneous multimedia data sources.

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Ontology for Multimedia Applications

In Binary Decision Diagram (BDD) based realization of logic circuits, the area and power consumption is determined by the total number of nodes of the BDD and the expected switching activity of the nodes A proper polarity selection of the subfunctions can not only reduce the number of BDD nodes, but also the switching For a multi-output function, more the sharing between the subfunctions, more is the reduction in the number of BDD nodes so also the power A Genetic Algorithm based output phase selection of the multi-output function (in BDD form) is proposed in this paper This idea when applied to a number of benchmark circuits, it is found to reduce the number of nodes in the BDD and hence the area and power A trade-off has also been done for combined area and power minimization, considering the node switching as the major candidate for power consumption It has been found that the proposed method minimizes the area by about 3% and power by about 14%

Output Phase Assignment for Area and Power Optimization in Multi-level Multi-output Combinational Logic Circuits

Xylem vessels play a pivotal role in plant adaptation to drought stress. In this paper, we propose a novel framework that associates automatic segmentation of xylem vessels with its morphological features as a quantitative proxy to predict drought stress response (DSR). We develop an image processing pipeline that comprises of low level processing which enables high-throughput detection of xylem vessels. With no prior information about its size and location, the proposed detection methodology gives an accuracy of 98%. The labelled data for DSR are either not available or are subjectively developed, which is a low-throughput and error prone task. We resolve this problem by employing simplex volume maximization (SiVM) algorithm. The convex representations obtained from SiVM for each xylem in microscopic images based on its shape factors are aggregated to get an automated scoring of the whole plant. Bhattacharya distance is then employed to obtain the divergence of these responses w.r.t. the control group. The proposed framework successfully captures the phenotypic difference between MTU-1010 (drought susceptible rice cultivar) and Sahbhagi Dhan (drought tolerant rice cultivar).

Phenotyping of xylem vessels for drought stress analysis in rice

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.

Multi-modal Information Integration for Document Retrieval

We present a novel predictive statistical framework to improve the performance of an Eigen Tracker which uses fast and efficient eigen space updates to learn new views of the object being tracked on the fly using candid co-variance free incremental PCA. The proposed system detects and tracks an object in the scene by learning the appearance model of the object online motivated by non-traditional uniform norm. It speeds up the tracker many fold by avoiding nonlinear optimization generally used in the literature.

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Santanu Chaudhury

Papers

Ontology for Multimedia Applications

Output Phase Assignment for Area and Power Optimization in Multi-level Multi-output Combinational Logic Circuits

Phenotyping of xylem vessels for drought stress analysis in rice

Multi-modal Information Integration for Document Retrieval

Online Improved Eigen Tracking