Physiological signals: The next generation authentication and identification methods!?

Throughout the last 40 years, the security breach caused by human error is often disregarded. To relief the latter problem, this article introduces a new class of biometrics that is founded on processing physiological personal features, as opposed to physical and behavioral features. After an introduction on authentication, physiological signals are discussed, including their advantages, disadvantages, and initial directives for obtaining them. This new class of authentication methods can increase biometrics’ robustness and enables cross validation. I close this article with a brief discussion in which a recap of the article is provided, law, privacy, and ethical issues are discussed, some suggestions for the processing pipeline of this new class of authentication methods are done, and conclusions are drawn

Interactive detection of incrementally learned concepts in images with ranking and semantic query interpretation

This research was performed in the GOOSE project, which is jointly funded by the MIST research program of the Dutch Ministry of Defense and the AMSN enabling technology program.The number of networked cameras is growing exponentially. Multiple applications in different domains result in an increasing need to search semantically over video sensor data. In this paper, we present the GOOSE demonstrator, which is a real-time general-purpose search engine that allows users to pose natural language queries to retrieve corresponding images. Top-down, this demonstrator interprets queries, which are presented as an intuitive graph to collect user feedback. Bottomup, the system automatically recognizes and localizes concepts in images and it can incrementally learn novel concepts. A smart ranking combines both and allows effective retrieval of relevant images.peer-reviewe

TNO at TRECVID 2013 : multimedia event detection and instance search

We describe the TNO system and the evaluation results for TRECVID 2013 Multimedia Event Detection (MED) and instance search (INS) tasks. The MED system consists of a bag-of-word (BOW) approach with spatial tiling that uses low-level static and dynamic visual features, an audio feature and high-level concepts. Automatic speech recognition (ASR) and optical character recognition (OCR) are not used in the system. In the MED case with 100 example training videos, support-vector machines (SVM) are trained and fused to detect an event in the test set. In the case with 0 example videos, positive and negative concepts are extracted as keywords from the textual event description and events are detected with the high-level concepts. The MED results show that the SIFT keypoint descriptor is the one which contributes best to the results, fusion of multiple low-level features helps to improve the performance, and the textual event-description chain currently performs poorly. The TNO INS system presents a baseline open-source approach using standard SIFT keypoint detection and exhaustive matching. In order to speed up search times for queries a basic map-reduce scheme is presented to be used on a multi-node cluster. Our INS results show above-median results with acceptable search times.This research for the MED submission was performed in the GOOSE project, which is jointly funded by the enabling technology program Adaptive Multi Sensor Networks (AMSN) and the MIST research program of the Dutch Ministry of Defense. The INS submission was partly supported by the MIME project of the creative industries knowledge and innovation network CLICKNL.peer-reviewe

Intuitionistic quantum logic of an n-level system

A decade ago, Isham and Butterfield proposed a topos-theoretic approach to quantum mechanics, which meanwhile has been extended by Doering and Isham so as to provide a new mathematical foundation for all of physics. Last year, three of the present authors redeveloped and refined these ideas by combining the C*-algebraic approach to quantum theory with the so-called internal language of topos theory (see arXiv:0709.4364). The goal of the present paper is to illustrate our abstract setup through the concrete example of the C*-algebra of complex n by n matrices. This leads to an explicit expression for the pointfree quantum phase space and the associated logical structure and Gelfand transform of an n-level system. We also determine the pertinent non-probabilisitic state-proposition pairing (or valuation) and give a very natural topos-theoretic reformulation of the Kochen--Specker Theorem. The essential point is that the logical structure of a quantum n-level system turns out to be intuitionistic, which means that it is distributive but fails to satisfy the law of the excluded middle (both in opposition to the usual quantum logic).Comment: 26 page

TNO at TDT2001: Language Model-Based Topic Detection

Topic detection is concerned with the unsupervised clustering of news stories over time. The TNO topic detection system is based on a language modeling approach. For the grouping of stories we combined a simple single pass method to establish an initial clustering and a reallocation method to stabilize the clusters within a certain allowed deferral period. The similarity of an incoming story Sn to an existing cluster C is defined as the average of the similarities of Sn to each story S i 2 C. These individual similarities are computed by taking the sum of the generative probabilities P (Sn jS i ) and P (S i jSn) where S i and Sn are modeled as unigram language models. Because these story language models are based on extremely sparse statistics, the word probabilities are smoothed using a background model