Learning to Find Eye Region Landmarks for Remote Gaze Estimation in Unconstrained Settings

Conventional feature-based and model-based gaze estimation methods have proven to perform well in settings with controlled illumination and specialized cameras. In unconstrained real-world settings, however, such methods are surpassed by recent appearance-based methods due to difficulties in modeling factors such as illumination changes and other visual artifacts. We present a novel learning-based method for eye region landmark localization that enables conventional methods to be competitive to latest appearance-based methods. Despite having been trained exclusively on synthetic data, our method exceeds the state of the art for iris localization and eye shape registration on real-world imagery. We then use the detected landmarks as input to iterative model-fitting and lightweight learning-based gaze estimation methods. Our approach outperforms existing model-fitting and appearance-based methods in the context of person-independent and personalized gaze estimation

Improving port hinterland connection capacity: a comparative study of Polish and Belgian cases

The study takes a comparative approach by investigating the situation in the hinterlands of two different port areas in Europe: Antwerp (Belgium) and Gdansk-Sopot-Gdynia agglomeration (Poland). Both port centres have an important road hinterland connection that faces competition from other alternative modes of freight transport. However, the Port of Antwerp is already one of the leading ports of the continent while the ports of Gdansk and Gdynia are at the stage of building their competitive position. Also the importance of inland waterways in the transport systems in these countries is different – Belgium has a functioning network of waterways while Poland still has to develop it. The Belgian case is the E313 motorway, which makes the connection between Antwerp and Li�ge and further on also Germany. The motorway has competition from both rail and inland waterways, especially in dealing with port-bound traffic. The Albert Canal, which runs mainly in parallel with the motorway, is currently being subject to capacity expansion through the extension and elevation of a number bridges that cross the canal. Rail could specifically benefit from the potential re-activation of the Iron Rhine - an almost parallel connection to the motorway E313 between Antwerp and the German Ruhr area. The Polish case is focused on possible scenarios of freight traffic between Baltic port centre of Gdansk and Gdynia with important international harbour and fast developing regional centre - Bydgoszcz-Torun. At present the main connections between those urban areas are the state road 1, section of motorway A1 and railway CE-65. Gdansk, Torun and Bydgoszcz are also linked with Vistula river (part of international inland waterways E-40 and E-70) but so far it is not used extensively. The cases are analyzed separately. The added value of the paper is the comparative analysis which allows making conclusions that are valid for both environments. The results are of high relevance to policy makers in charge of alleviating port hinterland problems, and also to ports in the current highly competitive environment.

The Selected Problems of Public Transport Organization Using Mathematical Tools on the Example of Poland

Public transport plays an increasingly important role in satisfying the transport needs. Travellers’ requirements regarding the quality of services are increasing. In addition to passenger comfort, other parameters are important (timetable and the state of transport infrastructure). Therefore, methods that determine the appropriate organization of public transport for an area should be sought. The purpose of the article is to present the most commonly used optimization methods and tools that have been applied to the chosen problems of organization of public transport mainly in Poland (described in the articles of mainly Polish scientists), but against the background of global research. The article characterizes the functioning of public transport in Poland. The selected problems of public transport functioning, which can be solved by using optimization methods and tools were discussed. The chosen methods that were used to formulate and solve the identified problems were indicated. The effects of this article will form part of the work on the POIR.01.01.01-00-0970/17-00 project "IT system for computer-aided public transport planning" financed by the National Centre for Research and Development

Shallow reading with Deep Learning: Predicting popularity of online content using only its title

With the ever decreasing attention span of contemporary Internet users, the title of online content (such as a news article or video) can be a major factor in determining its popularity. To take advantage of this phenomenon, we propose a new method based on a bidirectional Long Short-Term Memory (LSTM) neural network designed to predict the popularity of online content using only its title. We evaluate the proposed architecture on two distinct datasets of news articles and news videos distributed in social media that contain over 40,000 samples in total. On those datasets, our approach improves the performance over traditional shallow approaches by a margin of 15%. Additionally, we show that using pre-trained word vectors in the embedding layer improves the results of LSTM models, especially when the training set is small. To our knowledge, this is the first attempt of applying popularity prediction using only textual information from the title