Temat: moving object detection - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: A novel approach of voterank-based knowledge graph for improvement of multi-attributes influence nodes on social networks
Autorzy:: Pham, Hai Van
Duong, Pham Van
Tran, Dinh Tuan
Lee, Joo-Ho
Powiązania:: https://bibliotekanauki.pl/articles/23944825.pdf
Data publikacji:: 2023
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: video surveillance
deep learning
moving object detection
Opis:: Recently, measuring users and community influences on social media networks play significant roles in science and engineering. To address the problems, many researchers have investigated measuring users with these influences by dealing with huge data sets. However, it is hard to enhance the performances of these studies with multiple attributes together with these influences on social networks. This paper has presented a novel model for measuring users with these influences on a social network. In this model, the suggested algorithm combines Knowledge Graph and the learning techniques based on the vote rank mechanism to reflect user interaction activities on the social network. To validate the proposed method, the proposed method has been tested through homogeneous graph with the building knowledge graph based on user interactions together with influences in realtime. Experimental results of the proposed model using six open public data show that the proposed algorithm is an effectiveness in identifying influential nodes.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2023, 13, 3; 165--180
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Moving object detection for complex scenes by merging BG modeling and deep learning method
Autorzy:: Lin, Chih-Yang
Huang, Han-Yi
Lin, Wei-Yang
Ng, Hui-Fuang
Muchtar, Kahlil
Nurdin, Nadhila
Powiązania:: https://bibliotekanauki.pl/articles/23944823.pdf
Data publikacji:: 2023
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: video surveillance
deep learning
moving object detection
Opis:: In recent years, many studies have attempted to use deep learning for moving object detection. Some research also combines object detection methods with traditional background modeling. However, this approach may run into some problems with parameter settings and weight imbalances. In order to solve the aforementioned problems, this paper proposes a new way to combine ViBe and Faster-RCNN for moving object detection. To be more specific, our approach is to confine the candidate boxes to only retain the area containing moving objects through traditional background modeling. Furthermore, in order to make the detection able to more accurately filter out the static object, the probability of each region proposal then being retained. In this paper, we compare four famous methods, namely GMM and ViBe for the traditional methods, and DeepBS and SFEN for the deep learning-based methods. The result of the experiment shows that the proposed method has the best overall performance score among all methods. The proposed method is also robust to the dynamic background and environmental changes and is able to separate stationary objects from moving objects. Especially the overall F-measure with the CDNET 2014 dataset (like in the dynamic background and intermittent object motion cases) was 0,8572.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2023, 13, 3; 151--163
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Implementacja sprzętowa odejmowania tła metodą ViBe w układzie FPGA
Hardware implementation of the ViBe background subtraction method in FPGA
Autorzy:: Kryjak, T.
Gorgoń, M.
Powiązania:: https://bibliotekanauki.pl/articles/155000.pdf
Data publikacji:: 2013
Wydawca:: Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:: układy rekonfigurowalne FPGA
przetwarzanie i analiza obrazów
generacja tła
odejmowanie tła
segmentacja obiektów ruchomych
algorytm ViBe
FPGA
reconfigurable devices
image processing and analysis
background generation
background subtraction
moving object detection
ViBe algorithm
Opis:: W artykule zaprezentowano implementację sprzętową nowatorskiego algorytmu odejmowania tła ViBe (ang. VIsual Background Extractor) w układzie rekonfigurowalnym FPGA. Metoda ta opiera się na odmiennej od dotychczas opisywanych i realizowanych koncepcji modelowania tła. W pracy dokonano oceny możliwości przeniesienia algorytmu na platformę sprzętową, pokazano dwie modyfikacje, które pozwoliły poprawić działanie metody oraz omówiono zrealizowany system sprzętowy. Według wiedzy autorów jest to pierwszy opis implementacji tego algorytmu w układzie FPGA.
This paper presents a hardware implementation in the FPGA reconfigurable device of ViBe - a novel background subtraction algorithm. The method is based on a different, from those previously described and implemented, background modelling concept. It partly uses random numbers, which allowed us to significantly reduce the buffer size in relation to the standard methods like mean or median form a buffer. A detailed description of ViBe can be found in papers [6, 7, 8]. In this paper the role of background generation algorithms in image processing and analysis systems, with particular emphasis on hardware implementations is discussed (Section 1). The ViBe algorithm is described in Section 2. Then an analysis of the possibility of implementing ViBe in FPGA is presented (Section 3). Section 4 describes two proposed modifications: the use of the CIE Lab colour space and the enhanced flashing pixels detection method. Their desirability has been confirmed quantitatively using the "ChangeDetection" database [9]. A detailed description of the designed ViBe hardware module and image processing system is presented in Section 5. The scheme of the ViBe module is shown in Figure 5 and the whole system in Figure 4. Table 3 summarizes the hardware resource utilization. The proposed solution enables the detection of objects using the method ViBe and enables realtime processing of a colour 640 x 480 video stream at 60 frames per second. The obtained results confirm the high usefulness of FPGA in the implementation of advanced image processing and analysis algorithms.
Źródło:: Pomiary Automatyka Kontrola; 2013, R. 59, nr 11, 11; 1191-1194
0032-4140
Pojawia się w:: Pomiary Automatyka Kontrola
Dostawca treści:: Biblioteka Nauki

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