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The AfD's Winning Formula – No Need for Economic Strategy Blurring in Germany
Western European Populist Radical Right Parties (PRRPs) have addressed the dispersed socio-economic status of their electorates by blurring their economic positioning. This contribution analyses the rise of the German PRRP Alternative für Deutschland (AfD) between 2013 and 2017 and the role of its economic policy platform. In contrast to its European peers, the AfD shows few signs of economic strategy blurring. The party offers clear antiredistribution policies that are matched by AfD voters' preferences: even the least affluent AfD supporters have stronger preferences for lower redistribution than the most affluent non-AfD supporters. For AfD supporters with lower socio-economic positions this means that they support economic policies that are against their economic interests. Extreme authoritarian cultural policies spiced up with criticism of the establishment and combined with a general opposition to redistribution can be identified as the AfD's winning formula. Within the Western European PRRP party family, this winning formula directed at supporters with lower socioeconomic positions constitutes an exception.
Journal Article
Eye tracking in second language acquisition and bilingualism : a research synthesis and methodological guide
Eye Tracking in Second Language Acquisition and Bilingualism provides foundational knowledge and hands-on advice for designing, conducting, and analysing eye-tracking research in applied linguistics. Godfroid's research synthesis and methodological guide introduces the reader to fundamental facts about eye movements, eye-tracking paradigms for language scientists, data analysis, and the practicalities of building a lab. This indispensable book will appeal to undergraduate students learning principles of experimental design, graduate students developing their theoretical and statistical repertoires, experienced scholars looking to expand their own research, and eye-tracking professionals.
Book
AnimalTrack: A Benchmark for Multi-Animal Tracking in the Wild
Multi-animal tracking (MAT), a multi-object tracking (MOT) problem, is crucial for animal motion and behavior analysis and has many crucial applications such as biology, ecology and animal conservation. Despite its importance, MAT is largely under-explored compared to other MOT problems such as multi-human tracking due to the scarcity of dedicated benchmarks. To address this problem, we introduce AnimalTrack, a dedicated benchmark for multi-animal tracking in the wild. Specifically, AnimalTrack consists of 58 sequences from a diverse selection of 10 common animal categories. On average, each sequence comprises of 33 target objects for tracking. In order to ensure high quality, every frame in AnimalTrack is manually labeled with careful inspection and refinement. To our best knowledge, AnimalTrack is the first benchmark dedicated to multi-animal tracking. In addition, to understand how existing MOT algorithms perform on AnimalTrack and provide baselines for future comparison, we extensively evaluate 14 state-of-the-art representative trackers. The evaluation results demonstrate that, not surprisingly, most of these trackers become degenerated due to the differences between pedestrians and animals in various aspects (e.g., pose, motion, and appearance), and more efforts are desired to improve multi-animal tracking. We hope that AnimalTrack together with evaluation and analysis will foster further progress on multi-animal tracking. The dataset and evaluation as well as our analysis will be made available upon the acceptance.
Journal Article
Object Tracking Based on Satellite Videos: A Literature Review
Video satellites have recently become an attractive method of Earth observation, providing consecutive images of the Earth’s surface for continuous monitoring of specific events. The development of on-board optical and communication systems has enabled the various applications of satellite image sequences. However, satellite video-based target tracking is a challenging research topic in remote sensing due to its relatively low spatial and temporal resolution. Thus, this survey systematically investigates current satellite video-based tracking approaches and benchmark datasets, focusing on five typical tracking applications: traffic target tracking, ship tracking, typhoon tracking, fire tracking, and ice motion tracking. The essential aspects of each tracking target are summarized, such as the tracking architecture, the fundamental characteristics, primary motivations, and contributions. Furthermore, popular visual tracking benchmarks and their respective properties are discussed. Finally, a revised multi-level dataset based on WPAFB videos is generated and quantitatively evaluated for future development in the satellite video-based tracking area. In addition, 54.3% of the tracklets with lower Difficulty Score (DS) are selected and renamed as the Easy group, while 27.2% and 18.5% of the tracklets are grouped into the Medium-DS group and the Hard-DS group, respectively.
Journal Article
Been there, done that : reading animal signs
When Cole's visit with his friend Helena nears its end, he asks where all the wild animals are and she takes him on a trail, showing signs of beavers, snowshoe hares, eagles, and more along the way. Includes activities.
Book
Semi-supervised Visual Tracking of Marine Animals Using Autonomous Underwater Vehicles
In-situ visual observations of marine organisms is crucial to developing behavioural understandings and their relations to their surrounding ecosystem. Typically, these observations are collected via divers, tags, and remotely-operated or human-piloted vehicles. Recently, however, autonomous underwater vehicles equipped with cameras and embedded computers with GPU capabilities are being developed for a variety of applications, and in particular, can be used to supplement these existing data collection mechanisms where human operation or tags are more difficult. Existing approaches have focused on using fully-supervised tracking methods, but labelled data for many underwater species are severely lacking. Semi-supervised trackers may offer alternative tracking solutions because they require less data than fully-supervised counterparts. However, because there are not existing realistic underwater tracking datasets, the performance of semi-supervised tracking algorithms in the marine domain is not well understood. To better evaluate their performance and utility, in this paper we provide (1) a novel dataset specific to marine animals located at http://warp.whoi.edu/vmat/, (2) an evaluation of state-of-the-art semi-supervised algorithms in the context of underwater animal tracking, and (3) an evaluation of real-world performance through demonstrations using a semi-supervised algorithm on-board an autonomous underwater vehicle to track marine animals in the wild.
Journal Article
HOTA: A Higher Order Metric for Evaluating Multi-object Tracking
Multi-object tracking (MOT) has been notoriously difficult to evaluate. Previous metrics overemphasize the importance of either detection or association. To address this, we present a novel MOT evaluation metric, higher order tracking accuracy (HOTA), which explicitly balances the effect of performing accurate detection, association and localization into a single unified metric for comparing trackers. HOTA decomposes into a family of sub-metrics which are able to evaluate each of five basic error types separately, which enables clear analysis of tracking performance. We evaluate the effectiveness of HOTA on the MOTChallenge benchmark, and show that it is able to capture important aspects of MOT performance not previously taken into account by established metrics. Furthermore, we show HOTA scores better align with human visual evaluation of tracking performance.
Journal Article