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.

/pdf/data-clustering-a-review-4c452f5cab.pdf

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.

/pdf/online-and-off-line-handwriting-recognition-a-comprehensive-4qmt9ty596.pdf

Online and off-line handwriting recognition: a comprehensive survey

IEEE Transactions on Pattern Analysis and Machine Intelligence

Nature offers several examples of self-organizing
systems that automatically adjust to changing conditions without
adversely affecting the system goals. We propose a self-organizing
sensor network that is inspired from real-life systems for sampling a region in an energy-efficient manner. Mobile
nodes in our network execute certain rules by processing local information. These rules enable the nodes to divide the sampling task in a manner such that the nodes self-organize themselves to reduce the total power consumed and improve the accuracy with which the phenomena are sampled. The digital hormone-based model that encapsulates these rules, provides a theoretical framework for examining this class of systems. This model has been simulated and implemented on cricket motes. Our results indicate that the model is more effective than a conventional model with a fixed rate sampling.

https://downloads.hindawi.com/journals/je/2013/959430.pdf

Bio-Inspired Distributed Sensing Using a Self-Organizing Sensor Network

In this paper, we present a technique for distributed self-calibration of pan-tilt camera network using multi-layered belief propagation. Our goal is to obtain globally consistent estimates of the camera parameters for each camera with respect to a global world coordinate system. The network configuration changes with time as the cameras can pan and tilt. We also give a distributed algorithm for automatically finding which cameras have overlapping views at a certain point in time. We argue that using belief propagation it is sufficient to have correspondences between three cameras at a time for calibrating a larger set of (static) cameras with overlapping views. Our method gives an accurate and globally consistent estimate of the camera parameters of each camera in the network.

/pdf/distributed-calibration-of-pan-tilt-camera-network-using-hb7ikjer67.pdf

Distributed calibration of pan-tilt camera network using multi-layered belief propagation

The present work is part of ongoing effort to improve the performance of Gujarati character recognition. In the recent advancement in kernel methods, the novel concept of multiple kernel learning(MKL) has given improved results for many problems. In this paper, we present novel application of MKL for Gujarati character recognition. We have applied three different feature representations for symbols obtained after zone wise segmentation of Gujarati text. The MKL based classification is proposed, where the MKL is used for learning optimal combination of different features for classification. In addition MKL based classification results for different features is also presented. The multiclass classification is performed in Decision DAG framework. The comparison results in 1-Vs-1 framework and using KNN classifier is also presented. The experiments have shown substantial improvement in earlier results.

Use of MKL as symbol classifier for Gujarati character recognition

This paper describes a system for recognition of dynamic hand gestures. Appearance based and motion related features have been used for characterizing the gestures. Gesture sequences have been interpreted using an HMM based recognition engine. Interpreted gesture sequences have been translated into commands for controlling a remote robot.

A gesture based interface for remote robot control

This paper addresses the problem of invariant-based recognition of quadric configurations from a single image. These configurations consist of a pair of rigidly connected translationally repeated quadric surfaces. This problem is approached via a reconstruction framework. A new mathematical framework, using relative affine structure, on the lines of Luong and Vieville (1996), has been proposed. Using this mathematical framework, translationally repeated objects have been projectively reconstructed, from a single image, with four image point correspondences of the distinguished points on the object and its translate. This has been used to obtain a reconstruction of a pair of translationally repeated quadrics. We have proposed joint projective invariants of a pair of proper quadrics. For the purpose of recognition of quadric configurations, we compute these invariants for the pair of reconstructed quadrics. Experimental results on synthetic and real images, establish the discriminatory power and stability of the proposed invariant-based recognition strategy. As a specific example, we have applied this technique for discriminating images of monuments which are characterized by translationally repeated domes modeled as quadrics.

/pdf/reconstruction-based-recognition-of-scenes-with-3jzvhh5zl0.pdf

Santanu Chaudhury

Papers

Bio-Inspired Distributed Sensing Using a Self-Organizing Sensor Network

Distributed calibration of pan-tilt camera network using multi-layered belief propagation

Use of MKL as symbol classifier for Gujarati character recognition

A gesture based interface for remote robot control

Reconstruction-based recognition of scenes with translationally repeated quadrics