Content-based Video Retrieval by Integrating Spatio-Temporal and Stochastic Recognition of Events

As amounts of publicly available video data grow the need to query this data efficiently becomes significant. Consequently content-based retrieval of video data turns out to be a challenging and important problem. We address the specific aspect of inferring semantics automatically from raw video data. In particular, we introduce a new video data model that supports the integrated use of two different approaches for mapping low-level features to high-level concepts. Firstly, the model is extended with a rule-based approach that supports spatio-temporal formalization of high-level concepts, and then with a stochastic approach. Furthermore, results on real tennis video data are presented, demonstrating the validity of both approaches, as well us advantages of their integrated us

Vote buying revisited: implications for receipt-freeness

In this paper, we analyse the concept of vote buying based on examples that try to stretch the meaning of the concept. Which ex- amples can still be called vote buying, and which cannot? We propose several dimensions that are relevant to qualifying an action as vote buy- ing or not. As a means of protection against vote buying and coercion, the concept of receipt-freeness has been proposed. We argue that, in or- der to protect against a larger set of vote buying activities, the concept of receipt-freeness should be interpreted probabilistically. We propose a general definition of probabilistic receipt-freeness by adapting existing definitions of probabilistic anonymity to voting

Towards an Information Theoretic Analysis of Searchable Encryption (Extended Version)

Searchable encryption is a technique that allows a client to store data in encrypted form on a curious server, such that data can be retrieved while leaking a minimal amount of information to the server. Many searchable encryption schemes have been proposed and proved secure in their own computational model. In this paper we propose a generic model for the analysis of searchable encryptions. We then identify the security parameters of searchable encryption schemes and prove information theoretical bounds on the security of the parameters. We argue that perfectly secure searchable encryption schemes cannot be efficient. We classify the seminal schemes in two categories: the schemes that leak information upfront during the storage phase, and schemes that leak some information at every search. This helps designers to choose the right scheme for an application

Application of calibration masks to TV vidicon tube

Photographic application method devised for overlaying test pattern masks on TV camera vidicon tubes prints the mask within 0.0076 cm of the vertical and horizontal center lines of the tube face. Entire process, including mask fabrication and alignment procedure, requires less than 10 minutes

Image segmentation and feature extraction for recognizing strokes in tennis game videos

This paper addresses the problem of recognizing human actions from video. Particularly, the case of recognizing events in tennis game videos is analyzed. Driven by our domain knowledge, a robust player segmentation algorithm is developed real video data. Further, we introduce a number of novel features to be extracted for our particular application. Different feature combinations are investigated in order to find the optimal one. Finally, recognition results for different classes of tennis strokes using automatic learning capability of Hidden Markov Models (HMMs) are presented. The experimental results demonstrate that our method is close to realizing statistics of tennis games automatically using ordinary TV broadcast videos

Binary Biometrics: An Analytic Framework to Estimate the Bit Error Probability under Gaussian Assumption

In recent years the protection of biometric data has gained increased interest from the scientific community. Methods such as the helper data system, fuzzy extractors, fuzzy vault and cancellable biometrics have been proposed for protecting biometric data. Most of these methods use cryptographic primitives and require a binary representation from the real-valued biometric data. Hence, the similarity of biometric samples is measured in terms of the Hamming distance between the binary vector obtained at the enrolment and verification phase. The number of errors depends on the expected error probability Pe of each bit between two biometric samples of the same subject. In this paper we introduce a framework for analytically estimating Pe under the assumption that the within-and between-class distribution can be modeled by a Gaussian distribution. We present the analytic expression of Pe as a function of the number of samples used at the enrolment (Ne) and verification (Nv) phases. The analytic expressions are validated using the FRGC v2 and FVC2000 biometric databases

Adaptively Secure Computationally Efficient Searchable Symmetric Encryption

Searchable encryption is a technique that allows a client to store documents on a server in encrypted form. Stored documents can be retrieved selectively while revealing as little information as\ud possible to the server. In the symmetric searchable encryption domain, the storage and the retrieval are performed by the same client. Most conventional searchable encryption schemes suffer\ud from two disadvantages.\ud First, searching the stored documents takes time linear in the size of the database, and/or uses heavy arithmetic operations.\ud Secondly, the existing schemes do not consider adaptive attackers;\ud a search-query will reveal information even about documents stored\ud in the future. If they do consider this, it is at a significant\ud cost to updates.\ud In this paper we propose a novel symmetric searchable encryption\ud scheme that offers searching at constant time in the number of\ud unique keywords stored on the server. We present two variants of\ud the basic scheme which differ in the efficiency of search and\ud update. We show how each scheme could be used in a personal health\ud record system