Research on Object Tracking Based on Graph Model in Sports Video

2018 ◽  
Vol 11 (3) ◽  
pp. 1-14
Author(s):  
Zhexiong Cui ◽  
Jun Zhang ◽  
XiaoFei Zhang ◽  
Lishu Xu

This article is about object tracking based on graph modeling. Object tracking is usually initialized by object detection methods. The fundamental hypothesis is that the object's pattern can be separated from its surrounding background sufficiently. However, for some objects, e.g., the ball in broadcast soccer videos, it is hard to extract effective features to detect the ball in a single video frame. The strategy adopted here is to identify the object's candidate regions in several consecutive frames, and then use a graph to construct the relationship between candidate regions. Finally, a Viterbi algorithm is used to extract the optimal path of the graph as the object's trajectory. This process is called short-term tracking. Then, it is used to initialize a Kalman filter to perform long-term tracking. In the process of tracking, the tracked region is verified to determine whether tracking is a failure, and short-term tracking is restarted if a failure happens.

Genome ◽  
1989 ◽  
Vol 31 (1) ◽  
pp. 272-283 ◽  
Author(s):  
Donal A. Hickey ◽  
Bernhard F. Benkel ◽  
Charalambos Magoulas

Multicellular eukaryotes have evolved complex homeostatic mechanisms that buffer the majority of their cells from direct interaction with the external environment. Thus, in these organisms long-term adaptations are generally achieved by modulating the developmental profile and tissue specificity of gene expression. Nevertheless, a subset of eukaryotic genes are still involved in direct responses to environmental fluctuations. It is the adaptative responses in the expression of these genes that buffers many other genes from direct environmental effects. Both microevolutionary and macroevolutionary patterns of change in the structure and regulation of such genes are illustrated by the sequences encoding α-amylases. The molecular biology and evolution of α-amylases in Drosophila and other higher eukaryotes are presented. The amylase system illustrates the effects of both long-term and short-term natural selection, acting on both the structural and regulatory components of a gene–enzyme system. This system offers an opportunity for linking evolutionary genetics to molecular biology, and it allows us to explore the relationship between short-term microevolutionary changes and long-term adaptations.Key words: gene regulation, molecular evolution, eukaryotes, Drosophila, amylase.


Information ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 3
Author(s):  
Shuang Chen ◽  
Zengcai Wang ◽  
Wenxin Chen

The effective detection of driver drowsiness is an important measure to prevent traffic accidents. Most existing drowsiness detection methods only use a single facial feature to identify fatigue status, ignoring the complex correlation between fatigue features and the time information of fatigue features, and this reduces the recognition accuracy. To solve these problems, we propose a driver sleepiness estimation model based on factorized bilinear feature fusion and a long- short-term recurrent convolutional network to detect driver drowsiness efficiently and accurately. The proposed framework includes three models: fatigue feature extraction, fatigue feature fusion, and driver drowsiness detection. First, we used a convolutional neural network (CNN) to effectively extract the deep representation of eye and mouth-related fatigue features from the face area detected in each video frame. Then, based on the factorized bilinear feature fusion model, we performed a nonlinear fusion of the deep feature representations of the eyes and mouth. Finally, we input a series of fused frame-level features into a long-short-term memory (LSTM) unit to obtain the time information of the features and used the softmax classifier to detect sleepiness. The proposed framework was evaluated with the National Tsing Hua University drowsy driver detection (NTHU-DDD) video dataset. The experimental results showed that this method had better stability and robustness compared with other methods.


2017 ◽  
Vol 24 (2) ◽  
pp. 383-405 ◽  
Author(s):  
Laurynas NARUŠEVIČIUS

The purpose of this paper is to investigate the relationship between profitability of the Lithuanian banking sector and its internal and external determinants. We use the panel error correc­tion model to assess long-term and short-term determinants of items from bank income statements (net interest income, net fee and commission income and operating expenses). The results of the pooled mean group estimator show that bank size and real GDP are the main determinants in the long-term. Meanwhile, empirical examination suggests various variables as short-term determinants of income statement items. The pooled mean group estimation technique and the analysis of sepa­rate income statement items enable us to have a better insight into the Lithuanian banking sector and determinants of its revenue and expenses.


Author(s):  
Fumei He ◽  
Ke-Chiun Chang ◽  
Min Li ◽  
Xueping Li ◽  
Fangjhy Li

We used the Bootstrap ARDL method to test the relationship between the export trades, FDI and CO2 emissions of the BRICS countries. We found that China's foreign direct investment and the lag one period of CO2 emissions have a cointegration on exports. South Africa's foreign direct investment and CO2 emissions have a cointegration relationship with the lag one period of exports, and South Africa's the lag one period of exports and foreign direct investment have a cointegration relationship with the lag one period of CO2 emissions. But whether it is China or South Africa, these three variables have no causal relationship in the long-term. Among the variables of other BRICS countries, Russia is the only country showed degenerate case #1 in McNown et al. mentioned in their paper. When we examined short-term causality, we found that CO2 emissions and export trade showed a reverse causal relationship, while FDI and carbon emissions were not so obvious. Export trade has a positive causal relationship with FDI. Those variables are different from different situations and different countries.


2019 ◽  
Vol 4 (2) ◽  
pp. 110-118
Author(s):  
Muhamad Muin ◽  

This study aims to analyze the relationship between the rupiah exchange rate (RER) and the money supply (M1) on the outgrowth of the consumer price index (CPI) in Indonesia. The data used in this study are monthly data series from January 2005 to January 2019. The results of this empirical study shows that there is a relationship between RER and M1 on CPI in the long term and there is a correction in the short term balance (ECM) which is influenced by M1. All of these variables are significant at α = 5% and partly significant at α = 1%.


1990 ◽  
Vol 4 (2) ◽  
pp. 145-154 ◽  
Author(s):  
Steven H. Frierman ◽  
Robert S. Weinberg ◽  
Allen Jackson

The purpose of this investigation was twofold: to determine if individuals who were assigned specific, difficult goals perform better than those assigned “do your best” goals, and to examine the importance of goal proximity (longterm vs. short-term) on bowling performance. Subjects were 72 students enrolled in two beginning bowling courses at a 4-year university. They were matched according to baseline bowling averages and then randomly assigned to one of four goal-setting conditions. A 4 × 5 (Goal Condition × Trials) ANOVA with repeated measures on the last factor revealed a significant goal condition main effect, with the long-term goal group improving more than the do-your-best group. No other performance comparisons reached significance. Questionnaire data revealed that subjects in all three numerical goal conditions rated their level of confidence significantly higher than the do-your-best goal group in Week 1, but the long-term goal group displayed a significantly higher level of confidence than the other three goal groups in Week 4. All other questions indicated that all groups tried hard and were committed to and accepted their goals.


Forests ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 573 ◽  
Author(s):  
Óscar Rodríguez de Rivera ◽  
Antonio López-Quílez ◽  
Marta Blangiardo

Climatic change is expected to affect forest development in the short term, as well as the spatial distribution of species in the long term. Species distribution models are potentially useful tools for guiding species choices in reforestation and forest management prescriptions to address climate change. The aim of this study is to build spatial and spatio-temporal models to predict the distribution of four different species present in the Spanish Forest Inventory. We have compared the different models and showed how accounting for dependencies in space and time affect the relationship between species and environmental variables.


2009 ◽  
Vol 364 (1536) ◽  
pp. 3755-3771 ◽  
Author(s):  
Prahlad Gupta ◽  
Jamie Tisdale

Word learning is studied in a multitude of ways, and it is often not clear what the relationship is between different phenomena. In this article, we begin by outlining a very simple functional framework that despite its simplicity can serve as a useful organizing scheme for thinking about various types of studies of word learning. We then review a number of themes that in recent years have emerged as important topics in the study of word learning, and relate them to the functional framework, noting nevertheless that these topics have tended to be somewhat separate areas of study. In the third part of the article, we describe a recent computational model and discuss how it offers a framework that can integrate and relate these various topics in word learning to each other. We conclude that issues that have typically been studied as separate topics can perhaps more fruitfully be thought of as closely integrated, with the present framework offering several suggestions about the nature of such integration.


2019 ◽  
Vol 18 (1) ◽  
pp. 1-6
Author(s):  
Mélanie Gauché ◽  
Lucie Brard

We explored people’s views regarding the kind of relationship that can be expected and created using such websites. In the current study, we used the same scenario technique. Vignettes depicting the kind of relationship an individual expected to find through the use of an online dating service were created by orthogonal combination of five factors: (a) passion; that is, the level of personal, affective involvement in the relationship, (b) intimacy; that is, the type of relationship desired (friendship vs. intimate/sexual), (c) commitment; that is, the expected duration of the relationship (short term vs. long term), (d) the user’s gender, and (e) the user’s age. Three contrasted positions were found. A minority of participants considered that creating a relationship using dating services was never very easy. A plurality of participants considered that creating either long-term romantic relationships or short-term, more “utilitarian” relationships was considerably easier than creating either short-term romantic relationships or long-term, more “utilitarian” relationships. Another plurality of participants considered that creating any relationship was quite possible. These participants disconnected the commonly admitted association between the duration of a relationship and level of emotional involvement. In other words, they considered that creating a passionate but short-lived relationship was not more difficult than creating any other kind of relationships.


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