Onkar Ambekar

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Automatically verifying the identity of a person by means of biometrics (e.g., face and fingerprint) is an important application in our day-to-day activities such as accessing banking services and security control in airports. To increase the system reliability, several biometric devices are often used. Such a combined system is known as a multimodal(More)
The Support Vector Data Description (SVDD) has been introduced to address the problem of anomaly (or outlier) detection. It essentially fits the smallest possible sphere around the given data points, allowing some points to be excluded as outliers. Whether or not a point is excluded, is governed by a slack variable. Mathematically, the values for the slack(More)
Local Gabor features (jets) have been widely used in face recognition systems. Once the sets of jets have been extracted from the two faces to be compared, a proper measure of similarity (or distance) between corresponding features should be chosen. For instance, in the well known Elastic Bunch Graph Matching (EBGM) approach and other Gabor-based face(More)
Detecting the location and identity of users is a first step in creating context-aware applications for technologically-endowed environments. We propose a system that makes use of motion detection, person tracking, face identification, feature-based identification, audio-based localization, and audio-based identification modules, fusing information with(More)
The aim of this project is to monitor a room for the purposes of analysing the interactions and identities of a small set of individuals. We work with multiple uncalibrated sensors that observe a single environment and generate multimodal data streams. These streams are processed with the help of a generic client-server middleware called SmartFlow. Modules(More)
This report summarizes the result of the BioSEcure DS2 (Desktop) evaluation campaign. This campaign aims at evaluating multimodal fusion algorithms involving face, fingerprint and iris biometrics for person authentication, targeting at the application of physical access control in a medium-sized establishment with some 500 persons. While multimodal(More)
In this paper we will argue that sensor networks in which multimodal sensors are connected to each other and computational devices capable of data mining, offer the possibility of serendipitous and opportunistic sensing in which unanticipated associations are detected and used to produce more robust event recognition. To illustrate this point of view, we(More)
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