nils-herrmann/clean_scirepeval huggingface dataset:
Security pitfalls of frame-by-frame approaches to video watermarking

Watermarking digital video material is usually considered as watermarking a sequence of still images. However, such a frame-by-frame approach is very risky since straightforward embedding strategies can result in poor performance in terms of security i.e., against hostile attacks. As examples, two very common video-watermarking systems will be presented as well as the associated intra-video collusion attacks which defeat them. Then, both watermark modulation and embedding strength modulation will be surveyed to design alternative embedding strategies which exhibit superior performance against such attacks. Nevertheless, it will also be shown that an expert attacker can still construct an effective watermark removal attack. Finally, there will be a discussion to assert whether or not security against intra-video collusion can be achieved with such blind frame-by-frame embedding strategies.
Demographic classification: Do gender and ethnicity affect each other?

Gender and ethnicity classification are challenging topics in the field of face analysis. Some features, like skin color, are relevant only for ethnicity but not for gender; some others, like face geometry, are important for both. The impact of ethnicity in gender perception, as the effect of gender on ethnicity disambiguation, is not clear. This paper provides a study to check if gender and ethnicity affect each other during the classification. Three different well-established algorithms have been implemented to provide significant experiments. These algorithms are used for both gender and ethnicity classification. Ethnicity-specific gender classifiers are trained and tested using faces from a specific ethnicity; the accuracies achieved are compared with the ones obtained using generic gender classifiers, trained and tested with faces from different ethnic groups. With a similar procedure we compare gender-specific ethnicity classifiers, trained and tested selecting faces with a specific gender, with generic ethnicity classifiers, trained and tested with both male and female faces. The study shows that specific and generic classifiers perform equally. That means, for the features selected, gender and ethnicity do not affect each other.
Protection of 3D Object Visual Representations

In this paper, we describe a new framework for watermarking 3D objects via their contour information. Unlike most conventional 3D object watermarking techniques, for which both insertion and extraction of the mark are performed on the object itself (3D/3D approach), we propose an asymmetric 3D/2D procedure. The goal of our work is to retrieve information (originally hidden in the apparent 3D silhouette of the object) from resulting images or videos having used the synthetic object, thus protecting the visual representations of the object. After developing theoretical and practical key-points of this 3D object watermarking scheme, we present the results of some preliminary experiments
Apparent Age Estimation from Face Images Combining General and Children-Specialized Deep Learning Models

This work describes our solution in the second edition of the ChaLearn LAP competition on Apparent Age Estimation. Starting from a pretrained version of the VGG-16 convolutional neural network for face recognition, we train it on the huge IMDB-Wiki dataset for biological age estimation and then fine-tune it for apparent age estimation using the relatively small competition dataset. We show that the precise age estimation of children is the cornerstone of the competition. Therefore, we integrate a separate "children" VGG-16 network for apparent age estimation of children between 0 and 12 years old in our final solution. The "children" network is fine-tuned from the "general" one. We employ different age encoding strategies for training "general" and "children" networks: the soft one (label distribution encoding) for the "general" network and the strict one (0/1 classification encoding) for the "children" network. Finally, we highlight the importance of the state-of-the-art face detection and face alignment for the final apparent age estimation. Our resulting solution wins the 1st place in the competition significantly outperforming the runner-up.
Integrating facial makeup detection into multimodal biometric user verification system

Multimodal biometric fusion is generally used for increasing the verification accuracy by combining two or more biometric traits. Fusion systems with predefined constant weight values for each biometry becomes much popular. Among biometrics, face modality is one of the most common traits that is used in such fusion system. However, face verification suffers from many challenging difficulties, one of which is facial makeup. Recently, it has been shown that the accuracy of face verification can be impacted by the presence of facial makeup. And as such, the verification result of a multimodal fusion system with constant weight value for each biometry can be degraded by facial cosmetics. In this work, we propose a method of integrating facial makeup detection into the fusion system to increase performance. In our investigated scenario, score level fusion of face, fingerprint and iris verification are performed, while the weight value of each trait changes dynamically according to the level of makeup classification of test facial image. So far, this is the first work taking into account the facial makeup within a multimodal biometric verification system. Experiments on 1600 different subjects reveal that our proposed method can help in increasing the overall performance of fusion system than without using the facial makeup information.
Keynote speech 1: Bag of visual soft biometrics for person identification: New trends and challenges

In this talk we seek to provide insight on the general topic of visual soft biometrics (gender, age, ethnicity, etc.). First, we present a new refined definition of soft biometrics, emphasizing on the aspect of human compliance, and then proceed to identify candidate traits that accept this novel definition. Second, we introduce some image processing techniques related to the estimation of some traits (weight, color of clothes, make-up, age and gender). Third, we address relations between traits and discuss associated benefits and limitations of these traits. We consider a new application, namely human identification solely carried out by a bag of facial, body and accessory soft biometric traits, and as an evidence of its practicality, we provide preliminary promising results. Finally, we conclude our presentation by some of our on-going activities in the domain of facial aesthetics based on facial soft biometric traits.
Analysis and reproduction of facial expressions for communicating clones

We present a novel view-based approach to quantify and reproduce facial expressions, by systematically exploiting the degrees of freedom allowed by a realistic face model, which embeds efficient mesh morphing and texture animations to synthesize facial expressions. For this purpose, we propose to use eigenfeatures, built from synthetic images, and design a linear estimator to interpret the responses of the eigenfeatures on a facial expression in terms of animation parameters.
Classification of captured and recaptured images to detect photograph spoofing

In this paper, a new face anti-spoofing approach, which is based on analysis of contrast and texture characteristics of captured and recaptured images, is proposed to detect photograph spoofing. Since photo image is a recaptured image, it may show quite different contrast and texture characteristics when compared to a real face image. In a spoofing attempt, image rotation is quite possible. Therefore, in this paper, a rotation invariant local binary pattern variance (LBPV) based method is selected to be used. The approach is tested on the publicly available NUAA photo-impostor database, which is constructed under illumination and place change. The results show that the approach is competitive with other existing methods tested on the same database. It is especially useful for conditions when photos are held by hand to spoof the system. Since an LBPV based method is used, it is robust to illumination changes. It is non-intrusive and simple.
On the Need for Signal-Coherent Watermarks

Digital watermarking has been introduced in the 1990s as a complementary technology for copyright protection. In an effort to anticipate hostile behavior of adversaries, the research community is constantly introducing new attacks to benchmark watermarking systems. In this paper, we present a generic attack strategy based on block replacement. As multimedia content is often highly repetitive, the attack exploits signal's self-similarities to replace each signal block with another, perceptually similar one. Guided by the principles of the proposed attack framework, we implemented three attack algorithms for different types of multimedia content: video shots, audio tracks and still images. Finally, considering the effectiveness of the proposed algorithms, we identify the properties that a watermark should have to counter this attacking strategy
Person recognition using a bag of facial soft biometrics (BoFSB)

This work introduces the novel idea of using a bag of facial soft biometrics for person verification and identification. The novel tool inherits the non-intrusiveness and computational efficiency of soft biometrics, which allow for fast and enrolment-free biometric analysis, even in the absence of consent and cooperation of the surveillance subject. In conjunction with the proposed system design and detection algorithms, we also proceed to shed some light on the statistical properties of different parameters that are pertinent to the proposed system, as well as provide insight on general design aspects in soft-biometric systems, and different aspects regarding efficient resource allocation.
Probabilistic fusion of regional scores in 3D face recognition

Information fusion in biometrics mostly relates to multi-biometric systems which attempt to improve the performance of individual matchers: multi-sensor, multi-algorithm, multimodal, etc. However, in addition to these scenarios, the need for methods to fuse the individual regional classifiers has also emerged, due to the increasing number of region-based methods proposed to overcome expression and occlusion problems in face recognition. In this paper, we present a combination approach by converting the regional match scores into probabilities with the help of estimated regional confidence measures. Initially, face is broken into several segments and similarity and confidence scores are obtained. Then, the posteriori probabilities of the user being genuine are calculated in each region given these two scores. For this calculation, the conditional densities are obtained on the training samples by applying non-parametric kernel density estimation separately for different intervals of confidence levels. Experimental results demonstrate that the inclusion of the regional confidence measures via probabilistic conversion is much more advantageous when compared to weighted sum of original scores.
Evaluation of visual privacy filters impact on video surveillance intelligibility

Since privacy issues are becoming important with growth of the video surveillance, many tools are proposed for protection of personal privacy in the video. However, little is understood regarding the effectiveness of such tools and their effect on the underlying surveillance tasks. In this paper, we propose a subjective evaluation methodology that compares several popular privacy protection techniques applied to typical indoor surveillance video. We identify and analyze the tradeoff between the privacy preservation of these tools and the intelligibility of activities in the resulted surveillance video.
Open-set semi-supervised audio-visual speaker recognition using co-training LDA and Sparse Representation Classifiers

Semi-supervised learning is attracting growing interest within the biometrics community. Almost all prior work focuses on closed-set scenarios, in which samples labelled automatically are assumed to belong to an enrolled class. This is often not the case in realistic applications and thus open-set alternatives are needed. This paper proposes a new approach to open-set, semi-supervised learning based on co-training, Linear Discriminant Analysis (LDA) subspaces and Sparse Representation Classifiers (SRCs). Experiments on the standard MOBIO dataset show how the new approach can utilize automatically labelled data to augment a smaller, manually labelled dataset and thus improve the performance of an open-set audio-visual person recognition system.
Recent advances on metamaterials with applications in terminal and high gain array and reflector antennas

This paper presents recent advances in the design and applications of metamaterials: electromagnetic band gap, artificial magnetic conductor and LH surfaces. Miniaturised EBG surfaces are studied and implemented using closely-coupled double-layer topologies. Antenna characteristics are shown from a multi-frequency array (using non-uniform left handed (LH) superstrate), a compact mobile handset prototype (incorporating a thin flexible miniaturised EBG surface). Furthermore, the use in arrays and reflector antennas is discussed
Towards predicting real-time properties of a component assembly

This work addresses the prediction of timing properties of a component-based application already during the composition phase. At this stage, it is of vital importance to guarantee that the timing requirements (e.g. end-to-end deadlines) of a real-time application that is executed on a target system is satisfied. This is obtained by predicting the real-time behaviour of a component-based application. We extend an already existing scenario-based approach [J. Muskens et al. (2004)] with the possibility to model the behaviour of an application and the behavior of the underlying components. As a result, an application developer can reason accurately about the dynamic resource consumption and real-time properties of a component assembly. The modeling involves the specification of synchronization constraints for tasks and the simulation of application behaviour. A concluding case-study of video encoder development reveals that the approach is not only feasible but also addresses yet unsolved problems of task parallel execution and synchronization.
Realization of QoS management using negotiation algorithms for multiprocessor NoC

With the growing complexity of new multimedia applications and the parallel execution enabled by multiprocessor architectures, quality-of-service (QoS) management for modern network-on-chip (NoC) systems becomes relevant. This paper presents an approach for efficient usage of platform resources and simultaneously controlling overall system performance, when multiple applications are active. Therefore, on top of the conventional QoS, we introduce an algorithm for setting quality levels of parallel executed applications on a multiprocessor network-on-chip. The new concept is a hierarchical system, where an application manager negotiates with the resource management to jointly optimize the quality of individual and overall application settings. The proposed QoS manager concept was successfully evaluated by an experimental set-up, employing two independent video-object decoders, a background sprite decoder from the MPEG-4 standard and an abstract audio object. This simultaneous execution of four independent applications was mapped on a simulator based on AEthereal network and eight ARM7 processors executed with a clock-cycle true simulator. The proposed distributed QoS management decreases the complexity of the overall management and improves the transparency and responsibilities in the decision taking
A comparative study of lossless coding techniques for screened continuous-tone images

The huge sizes of screened colour-separated photographic images makes lossless compression very beneficial for both storage and transmission. Because of the special structure induced by the half-tone dots, the compression results obtained on the CCITT test images might not apply to high-resolution screened images and the default parameters of existing compression algorithms may not be optimal. In this paper we compare the performance of different classes of lossless coders: general-purpose one-dimensional coders, non-adaptive two-dimensional black-and-white coders and adaptive two-dimensional coders. Firstly, experiments on a set of test images screened under different conditions showed that MGBILEVEL and JBIG perform best with respect to compression efficiency; the difference with the other coders is significant. Secondly, we investigated the influence of the screening method (stochastic or classical screening) and screening resolution on the compression ratio for these techniques.
Terahertz applications and technology

Research has been carried out in the THz region for several decades. Until fairly recently, the main drive came from applications such as radio astronomy, later followed by planetary, cometary and atmospheric science. Arguably, without these driving influences it is unlikely that many of the recent technological breakthroughs would have occurred. This paper presents an overview of space and terrestrial related applications and technologies. The more traditional and some most likely future applications will be treated.
Image Retrieval Simulations for the GEO Atmospheric Sounder (GAS)

The GEO atmospheric sounder (GAS) is a potential European future instrument, which utilizes interferometric synthetic aperture radiometry to obtain the desired spatial (30 km) and temporal (30 minutes) resolution for measurement of atmospheric temperature and humidity profiles under all weather conditions. This paper presents a simulation model for the entire imaging process. It enables detailed simulation of the impact of the instrument characteristics on the imaging performance. The model has been used as a tool to predict the performance of an instrument demonstrator under development.
Spatial inefficiency of MaxWeight scheduling

MaxWeight scheduling has gained enormous popularity as a powerful paradigm for achieving queue stability and maximum throughput in a wide variety of scenarios. The maximum-stability guarantees however rely on the fundamental premise that the system consists of a fixed set of flows with stationary ergodic traffic processes. In the present paper we examine networks where the population of active flows varies over time, as flows eventually end while new flows occasionally start. We show that MaxWeight policies may fail to provide maximum stability due to persistent inefficient spatial reuse. The intuitive explanation is that these policies tend to serve flows with large backlogs, even when the resulting spatial reuse is not particularly efficient, and fail to exploit maximum spatial reuse patterns involving flows with smaller backlogs. These results indicate that instability of MaxWeight scheduling can occur due to spatial inefficiency in networks with fixed transmission rates, which is fundamentally different from the inability to fully exploit time-varying rates shown in prior work. We discuss how the potential instability effects can be countered by spatial traffic aggregation, and describe some of the associated challenges and performance trade-offs.
Applications of Electromagnetic Crystals in Microstrip Technology

Recently, new promising periodic structures called Photonic Crystals, or more generally Electromagnetic Crystal structures, have been considered for both microwave and photonic applications. Planar microstrip waveguides are very attractive in microwave engineering where several innovative designs have been proposed to expand the scope of application of the new Photonic Crystal concepts to the well established microwave domain. Recent configurations are presented for these new promising applications both in microwave and millimetre wave integrated circuits and antennas.
Silicon Photonics Technology Platform for integration of optical IOs with ASICs

We highlighted Silicon Photonics Technology Platform and its scalability to increased data rates, higher interconnect densities and low system level power dissipation. • Silicon photonics has been in production since 2009 and has shipped > 500K+ chipsets for use in High Performance Computing and Datacenters. • We made the trade-off between hybrid and monolithic integration of photonics and electronics. Hybrid Silicon Photonics allows cost effective integration of photonics with advanced electronic nodes. • By integrating 3rd Party IP in the electronic IC, hybrid integration enables a first level of ASIC integration with Photonics. • A next level of ASIC integration is enabled by a “Silicon Photonics Interposer” where photonic capabilities are combined with hybrid integration with electronics and TSV technology.
Grass Field Detection for TV Picture Quality Enhancement

Current TV image enhancement can be improved if the image is analyzed, objects of interest are segmented, and each segment is processed with content-specific enhancement algorithms. In this paper we present an algorithm for segmenting grass areas in video sequences. The system employs multi-scale texture analysis and adaptive color and position models for computing a pixel-based soft segmentation map. Compared to previously reported algorithms, our system shows a clear improvement in the detection result: at 10% false positive rate, the true positive rate of our algorithm yields 91%, vs. 66% and 58% of two existing methods.
Enhanced antenna performances using planar circularly symmetric EBGs

Planar circularly symmetric (PCS) electromagnetic band-gap (EBG) substrates have recently been proposed to suppress surface waves (Llombart, N. et al., 2004). The application of PCS-EBG to reduce the surface waves excited by an antenna printed on a dielectric slab is discussed. The study starts from a reference microstrip-excited, slot-coupled dipole that presents a relatively large bandwidth (about 12%) and relatively low efficiency (about 40%-60%) due to surface wave losses. Some design considerations on how to enhance the performance of this antenna by surrounding it with a PCS-EBG are then presented. Finally the measured results are presented. These explicitly show the advantages of the proposed EBG substrate in terms of bandwidth and radiation pattern. A bandwidth of 20% is achieved without significant surface wave losses. The results also show radical improvements in the isolation between antennas printed on the same substrate.
IP-recovery in the DVB-H link layer for TV on mobile

In the nearby future, DVB-H Internet protocol based TV on mobile will be available in mobile devices. Due to transmission over error-prone channels, IP-datagrams may be corrupted. The DVB-H link layer is equipped with forward error correction (FEC), allowing correction of defect IP-datagrams, using two-bit signaling. Locators are applied to find correctly received IP-datagrams and possible corrected IP-datagrams, for the situation that forward error correction fails to correct all incorrectly received IP-datagrams. Experimental research has shown that for the situation that the received data cannot be fully corrected by the FEC, considerable number of IP-datagrams can be recovered using the locator information. The successful recovery depends on the received IP-datagram length and the error probability and results in an improved audiovisual decoding quality.