scholarly journals Deep Learning-Based Multitarget Motion Shadow Rejection and Accurate Tracking for Sports Video

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Chunxia Duan
Keyword(s):  
Regional Growth ◽  
Growth Function ◽  
Target Object ◽  
Multitarget Tracking ◽  
Image Frame ◽  
Sports Video ◽  
Optical Flow Method ◽  
Target Action ◽  
Target Frame ◽  
Sports Videos

The effect is tested in various specific scenes of sports videos to complete the multitarget motion multitarget tracking detection application applicable to various specific scenes within sports videos. In this paper, deep neural networks are applied to sports video multitarget motion shadow suppression and accurate tracking to improve tracking performance. After the target frame selection is determined, the tracker uses an optical flow method to estimate the limits of the target sports video multitarget motion based on the sports video multitarget motion of the target object between frames. The detector first scans each sports video image frame one by one, observing the previously discovered and learned image frame subregions one by one until the current moment that is highly like the target to be tracked. The preprocessed remote sensing images are converted into grayscale images, the histogram is normalized, and the appropriate height threshold is selected in combination with the regional growth function to realize the rejection of sports video multitarget motion shadow and establish the sports video multitarget network model. The distance and direction of the precise target displacement are determined by frequency-domain vectors and null domain vectors, and the target action judgment mechanism is formed by decision learning. Finally, comparing with other shadow rejection and precision tracking algorithms, the proposed algorithm achieves greater advantages in terms of accuracy and time consumption.

scholarly journals Shot Classification of Field Sports Videos Using AlexNet Convolutional Neural Network

2019 ◽  
Vol 9 (3) ◽  
pp. 483 ◽  
Author(s):  
Rabia A. Minhas ◽  
Ali Javed ◽  
Aun Irtaza ◽  
Muhammad Tariq Mahmood ◽  
Young Bok Joo
Keyword(s):  
Neural Network ◽  
Content Analysis ◽  
Support Vector ◽  
Video Content ◽  
Video Content Analysis ◽  
Sports Video ◽  
Analysis Techniques ◽  
Shot Classification ◽  
Sports Videos ◽  
Field Sports

Broadcasters produce enormous numbers of sport videos in cyberspace due to massive viewership and commercial benefits. Manual processing of such content for selecting the important game segments is a laborious activity; therefore, automatic video content analysis techniques are required to effectively handle the huge sports video repositories. The sports video content analysis techniques consider the shot classification as a fundamental step to enhance the probability of achieving better accuracy for various important tasks, i.e., video summarization, key-events selection, and to suppress the misclassification rates. Therefore, in this research work, we propose an effective shot classification method based on AlexNet Convolutional Neural Networks (AlexNet CNN) for field sports videos. The proposed method has an eight-layered network that consists of five convolutional layers and three fully connected layers to classify the shots into long, medium, close-up, and out-of-the-field shots. Through the response normalization and the dropout layers on the feature maps we boosted the overall training and validation performance evaluated over a diverse dataset of cricket and soccer videos. In comparison to Support Vector Machine (SVM), Extreme Learning Machine (ELM), K-Nearest Neighbors (KNN), and standard Convolution Neural Network (CNN), our model achieves the maximum accuracy of 94.07%. Performance comparison against baseline state-of-the-art shot classification approaches are also conducted to prove the superiority of the proposed approach.

Identifikasi Peran dan Strategi Pelabuhan Bebas Sabang

2020 ◽  
Vol 4 (3) ◽  
pp. 167-178
Author(s):  
Zurayna Sari
Keyword(s):  
Economic Development ◽  
Descriptive Analysis ◽  
Regional Growth ◽  
Maintenance Strategy ◽  
Regional Economic ◽  
Growth Center ◽  
Free Port ◽  
And Function ◽  
Role And Function

ABSTRAKPelabuhan berperan sebagai fasilitas penunjang pusat pertumbuhan regional dalam proses pembangunan ekonomi wilayah. Pelabuhan Bebas Sabang diarahkan sebagai pusat pertumbuhan ekonomi regional dan diharapkan dapat meningkatkan perekonomian Kawasan Sabang. Permasalahan yang dihadapi Pelabuhan Bebas Sabang adalah belum optimalnya peran dan fungsi Pelabuhan Bebas Sabang dalam menunjang perekonomian wilayah. Penelitian ini bertujuan untuk mengetahui peran Pelabuhan Bebas Sabang dalam mendorong perkembangan perekonomian Kawasan Sabang. Lingkup materi yang dibahas mencakup peran-peran Pelabuhan Bebas Sabang, menentukan potensi dan masalah serta upaya-upaya peningkatan peran Pelabuhan Bebas Sabang. Metode analisis yang dilakukan adalah analisis deskriptif dengan pendekatan analisis data kualitatif dan kuantitatif. Alat analisis yang digunakan adalah analisis SWOT IFAS-EFAS. Hasil analisis menunjukkan dalam kurun waktu 4 (empat) tahun terakhir dari tahun 2010-2013, Pelabuhan Bebas Sabang belum optimal dalam menjalankan perannya, sehingga membutuhkan strategi pengembangan dengan pendekatan Agressive Maintenance Strategy (strategi perbaikan agresif), yaitu strategi konsolidasi internal dengan memperbaiki faktor-faktor kelemahan untuk memaksimalkan pemanfaatan peluang.Kata kunci: Pengelolaan, SWOT IFAS-EFAS, WilayahABSTRACTPort was supporting facility of regional growth center in the process of regional economic development. Sabang free port was directed as the center of regional economic growth and expected to raise the economy of sabang. Problems faced by sabang free port was yet optimal role and function in supporting the economy of the region. This study aimed to determine the role of sabang free port in supporting the economic development of sabang. The covered material scope included roles of sabang free port, determining the potentials and problems and efforts of increasing the role of sabang free port. The method of analysis was descriptive analysis with qualitative and quantitative approach. The analytical tool used was the swot ifas-efas analysis. The analysis results showed in the period of 4 (four) years from 2010 until 2013, sabang free port was not optimal in carrying out its role yet, so it requires development strategies with agressive maintenance strategy approach, which is internal consolidation strategy by improving vulnerability factors to maximize the utilization of opportunities.Keywords:, Management, Regional, SWOT IFAS-EFAS

Hierarchical composition in complex object drawing

2019 ◽  
Author(s):  
Michiru Makuuchi
Keyword(s):  
Hierarchical Structure ◽  
Homo Sapiens ◽  
Hierarchical Structures ◽  
Target Object ◽  
Point Of View ◽  
Complex Object ◽  
Complex Objects ◽  
Cognitive Domains ◽  
Adult Participants ◽  
Symbolic Cognition

Symbolic behaviours such as language, music, drawing, dance, etc. are unique to humans and are found universally in every culture on earth1. These behaviours operate in different cognitive domains, but they are commonly characterised as linear sequences of symbols2,3. One of the most prominent features of language is hierarchical structure4, which is also found in music5,6 and mathematics7. Current research attempts to address whether hierarchical structure exists in drawing. When we draw complex objects, such as a face, we draw part by part in a hierarchical manner guided by visual semantic knowledge8. More specifically, we predicted how hierarchical structure emerges in drawing as follows. Although the drawing order of the constituent parts composing the target object is different amongst individuals, some parts will be drawn in succession consistently, thereby forming chunks. These chunks of parts would then be further integrated with other chunks into superordinate chunks, while showing differential affinity amongst chunks. The integration of chunks to an even higher chunk level repeats until finally reaching the full object. We analysed the order of drawing strokes of twenty-two complex objects by twenty-five young healthy adult participants with a cluster analysis9 and demonstrated reasonable hierarchical structures. The results suggest that drawing involves a linear production of symbols with a hierarchical structure. From an evolutionary point of view, we argue that ancient engravings and paintings manifest Homo sapiens’ capability for hierarchical symbolic cognition.

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