Santanu Chaudhury

Bio: Santanu Chaudhury is an academic researcher from Indian Institute of Technology, Jodhpur. The author has contributed to research in topics: Ontology (information science) & Image segmentation. The author has an hindex of 28, co-authored 380 publications receiving 3691 citations. Previous affiliations of Santanu Chaudhury include Central Electronics Engineering Research Institute & Indian Institute of Technology Delhi.

Real-Time Distributed Multi-object Tracking in a PTZ Camera Network

Abstract: A visual surveillance system should have the ability to view an object of interest at a certain size so that important information related to that object can be collected and analyzed as the object moves in the area observed by multiple cameras. In this paper, we propose a novel framework for real-time, distributed, multi-object tracking in a PTZ camera network with this capability. In our framework, the user is provided a tool to mark an object of interest such that the object is tracked at a certain size as it moves in the view of various cameras across space and time. The pan, tilt and zoom capabilities of the PTZ cameras are leveraged upon to ensure that the object of interest remains within the predefined size range as it is seamlessly tracked in the PTZ camera network. In our distributed system, each camera tracks the objects in its view using particle filter tracking and multi-layered belief propagation is used for seamlessly tracking objects across cameras.

3DTV view generation with virtual pan/tilt/zoom functionality

Abstract: This paper presents a novel rendering algorithm based on depth image warping to support virtual pan-tilt-zoom (PTZ) functionalities during 3D view generation. A method based on "3D-ness" knob is proposed for automatically specifying the virtual camera positions along a path, to model the PTZ mechanism in projective framework. Two novel quality enhancing techniques based on segmentation cues are proposed to add pan, tilt and zoom capabilities during arbitrary view synthesis. In addition to reduce the computational load that results in providing such functionalities, a novel selective warping scheme is presented to reduce the computational cost by as much as 40% while maintaining an acceptable quality of rendering results. Experiments are performed using standard "Breakdancers" and "Ballet" video sequences to demonstrate the effectiveness of the proposed methods as compared to currently published results.

Pàtrà: A Novel Document Architecture for Integrating Handwriting with Audio-Visual Information

Abstract: In this paper we present Patra - an integrated document architecture which incorporates handwritten illustrations captured and rendered in a temporal fashion synchronized with audio, video, text, and image data. The architecture of Patra permits non-linear growth in the form of multiple hierarchically organized play streams. Semantic metadata is also an integral part of Patra which serves a useful purpose of organizing such documents in a collection. We have developed an email application in which the users are provided with an authoring and rendering environment to compose, view, and reply to messages in the form of Patra.

Content directed enhancement of degraded document images

Abstract: Most of the document pre-processing techniques are parameter dependent. In this paper, we present a novel framework that learns optimal parameters, depending on the nature of the document image content for binarization and text/graphics segmentation. The learning problem has been formulated as an optimization problem using EM algorithm to adaptively learn optimal parameters. Experimental results have established the effectiveness of our approach.

Content Based Re-ranking Scheme for Video Queries on the Web

Abstract: We present a novel content-based re-ranking scheme for enhancing the precision of video retrieval on the Web. We use ontology specified knowledge of the video domain to map user queries to domain-based concepts. The user preferences are learned implicitly from the web logs of users' interaction with a video search engine. A ranking SVM is trained for each concept to learn the ranking function which incorporates user preferences for the concept. The videos are represented by a set of ingeniously derived content- based features which are based on MPEG-7 descriptors. Our re-ranking scheme thus effectively re-ranks results for new text queries submitted to our video retrieval system, leading to better satisfaction of the users' information need.

Data clustering: a review

Abstract: 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.

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

Abstract: 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.

Online and off-line handwriting recognition: a comprehensive survey

Abstract: 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.