Wydawnictwa Uczelniane / TUL Press

Stały URI zbioruhttp://hdl.handle.net/11652/17

Przeglądaj

Filtry

2018 - 201932020 - 20211

Ustawienia

Autorsearch.filters.applied.operator.equals: search.filters.author.Daszuta, Marcin

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Teraz wyświetlane 1 - 4 z 4
  • Pozycja
    Prediction of Natural Image Saliency for Synthetic Images
    (Wydawnictwo Politechniki Łódzkiej, 2021) Rudak, Ewa; Rynkiewicz, Filip; Daszuta, Marcin; Sturgulewski, Łukasz; Lazarek, Jagoda
    Numerous saliency models are being developed with the use ofneural networks and are capable of combining various features and predicting the saliency values with great results. In fact, it might be difficult to replace the possibilities of artificial intelligence applied to algorithms responsible for predicting saliency. However, the low-level features are still important and should not be removed completely from new saliency models. This work shows that carefully chosen and integrated features, including a deep learning based one, can be used for saliency prediction. The integration is obtained by using Multiple Kernel Learning. This solution is quite effective, as compared to a few other models tested on the same dataset.
  • Pozycja
    Classification of Objects in a Point Cloud using Neural Networks
    (Wydawnictwo Politechniki Łódzkiej, 2019) Daszuta, Marcin; Napieralska-Juszczak, Ewa
    3-dimensional scans captured in shape of point clouds are widely used in many dierent areas. Every such area use dierent kinds of sensors to ac-quire point clouds and do the analysis of the data but each of those needs some preanalysis to be done. One of the most important is segmentation and classification of points into types of objects. Such information considerably widens possibilities of usage for further purposes. There are many classifiers and many features based on which labeling can be done. In this paper few most commonly used approaches were chosen to check the influence of neighboring points acquisition on classification process. Results proof significant relation between those two steps of point cloud analysis. Visualization of analyzed point cloud also shown that precision of predictions not always comes with better visibility of certain types of objects. Additionally, color-less analysis of geometrical features seems to be promising way for further research.
  • Pozycja
    Pupil Detection Methods for Eye Tracking
    (Wydawnictwo Politechniki Łódzkiej, 2018) Rynkiewicz, Filip; Daszuta, Marcin; Napieralski, Piotr
    The theory that pupillary changes can reflect human psychophysical character was confirmed in several conducted studies. Authors of those studies have used devices called eye trackers in order to measure pupillary changes, blinking rate, eye movement patterns or even a gaze position. The main goal of those apparatuses is to locate the pupil on a given image using implemented pupil detection algorithms. In this paper the main focus will be set on several states of art pupil detection methods. All represent different approaches to performing the same tasks in difficult situations for ex.: low/high condition, low image resolutions or low contrast.
  • Pozycja
    Affective Pathfinding in Video Games
    (Wydawnictwo Politechniki Łódzkiej, 2018) Daszuta, Marcin; Wróbel, Filip; Rynkiewicz, Filip; Szajerman, Dominik; Napieralski, Piotr
    To allow player submerge in created environment of a video game, agents called Non-Player Characters (NPCs) should act believably. One of the most vital aspect, in case of NPCs is pathfinding. There are a few methods that allow change path finding algorithms to become more human-like. Yet, those are not considering many vital aspects of human decisions regarding path choosing. The main purpose of this paper is to present known approaches and show example of a new approach that wider considers psychological aspects of decision making in case of choosing a path.