scholarly journals REAL-TIME TRACKING IN SATELLITE VIDEOS VIA JOINT DISCRIMINATION AND POSE ESTIMATION

2019 ◽  
Vol XLII-2/W12 ◽  
pp. 23-29
Author(s):  
X. Chen ◽  
H. Sui
Keyword(s):  
Kalman Filter ◽  
Pose Estimation ◽  
Road Traffic ◽  
State Of The Art ◽  
Spatial Distance ◽  
Large Area ◽  
Background Region ◽  
Long Distance ◽  
The Road ◽  
Art Methods

<p><strong>Abstract.</strong> Object tracking has gained much attention in the field of computer vision and intelligent traffic analysis. Satellite videos are more suitable for long-distance tracking comparing to the road traffic videos. However, most of the state-of-the-art methods produce poor results when applied to satellite videos, due to low resolution of the small target and interference from similar background in satellite videos. In this paper, we present an improved Discriminative Correlation Filter based approach specifically tailored for small objects tracking in satellite videos through applying spatial weight in the filter and estimating the pose by Kalman filter. First, a spatial mask is introduced to encourage the final filter to give different contributions depending on the spatial distance. Furthermore, Kalman filter is incorporated into the approach with the aim of predicting the position when the target run into the large area similar background region. Finally, an efficient strategy for combining the improved DCF tracker and pose estimation is proposed. Experimental results on three satellite videos describing the traffic conditions of three cities demonstrate that the proposed approach can effectively track the targets even though the targets are similar to the background region in a period of time. Compare with other state-of-the-art methods, the final accuracies and speeds of our method achieve the best.</p>

scholarly journals Specifics of road safety inspection in tunnels

2021 ◽  
Vol 67 (3) ◽  
pp. 33-38
Author(s):  
Emir Smailovic ◽  
Boris Antić ◽  
Dalibor Pešić ◽  
Slaviš Beronja
Keyword(s):  
Energy Efficiency ◽  
Road Safety ◽  
Traffic Accident ◽  
Road Network ◽  
Road Traffic ◽  
State Of The Art ◽  
Safety Standards ◽  
The Road ◽  
Road Users ◽  
Road Tunnels

Tunnels are underground passages, placed horizontally, which serve to lead the road through them. In order to fulfill its purpose in road traffic, the tunnel must fit into the traffic infrastructure and as such not create an obstacle in movement and enable the movement of vehicles from entrance to exit without danger, but with increased restriction of freedom of lateral evacuation. Tunnels are among some of the most risky parts of the road network, primarily due to space constraints, where there is a possibility of a traffic accident. Managing the risks associated with the passage of road traffic, and in particular the safety of traffic in tunnels, is a serious problem in many countries. With the growing number of road users, it is necessary to adopt stricter standards regarding road tunnels. In addition to meeting these safety standards, factors such as operational requirements, economic efficiency, energy efficiency and state-of-the-art technology should also be taken into account when planning and equipping tunnels.

scholarly journals A macroscopic and hierarchical location model of regional road traffic disaster relief material repository

2019 ◽  
Vol 11 (1) ◽  
pp. 168781401882176 ◽  
Author(s):  
Jianfeng Xi ◽  
Kai Mu ◽  
Tongqiang Ding ◽  
Chengyuan Zhang ◽  
Hongyu Guo
Keyword(s):  
Ant Colony Algorithm ◽  
Road Traffic ◽  
Disaster Relief ◽  
Location Model ◽  
Large Area ◽  
Coverage Area ◽  
Location Selection ◽  
The Road ◽  
Hierarchical Location

Since the disaster point of road traffic emergency and the emergency demand were uncertain, the demand weighting model and the hierarchical location model are suitable for the characteristics of road traffic emergency. According to the requirements for coverage area of the macroscopic-location of the large area of disaster relief material repository, the demand weighting model and the hierarchical location model were established in this article. Among them, the demand weight model was solved by modeling, and the demand weight of each disaster point was obtained; the location model was combined with immune algorithm and ant colony algorithm to get the hierarchical location scheme. Finally, Jing-jin-ji that represented China’s “capital circle” was taken as an example, the model was solved using MATLAB, the mathematical software, and provided scientific and reasonable decision-making support for location selection. Moreover, it also provided a basis for the classification of the road traffic disaster relief material repository.

scholarly journals Crashed Electric Vehicle Handling and Recommendations—State of the Art in Germany

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1040 ◽  
Author(s):  
Katharina Wöhrl ◽  
Christian Geisbauer ◽  
Christoph Nebl ◽  
Susanne Lott ◽  
Hans-Georg Schweiger
Keyword(s):  
Electric Vehicles ◽  
Road Traffic ◽  
State Of The Art ◽  
Natural Increase ◽  
Vehicle Handling ◽  
The Road ◽  
Live Feed ◽  
Safe State ◽  
Near Future ◽  
High Voltage System

In the near future, electric powered vehicles will represent a major part of the road traffic. Accordingly, there will be a natural increase of accidents involving electric vehicles. There are not many cases of such accidents yet and therefore the experience and correct handling are still partially open points for the involved parties, such as the rescue services for example. The aim of this work is to provide a complete overview of the accident handling sequence in Germany, starting with the damaged vehicle on site and moving on to the risks and challenges for the stakeholders, such as transport and recycling companies. Arising from the developed overview, a handling recommendation for yet undiscussed points is given. Especially, different extinguishing and deactivation methods are compared and discussed. Due to a lack of a common live-feed from battery data on site, other criteria have to be taken into account to assess the state of the battery. The wrecked vehicle—including the high voltage system—needs to be in a definite safe state at the handover to a towing service. Depending on the case, different options for securing the vehicle will be considered in this work.

Industrial-Scale Production of High-Quality Graphene Sheets by Millstone Grinders

2021 ◽  
Author(s):  
Peng Lv ◽  
Xiaoshi Li ◽  
Zihan Zhang ◽  
Biao Nie ◽  
Yiliang Wu ◽  
...  
Keyword(s):  
Large Scale ◽  
State Of The Art ◽  
The State ◽  
Industrial Scale ◽  
Graphene Sheets ◽  
Scale Production ◽  
Large Area ◽  
High Quality ◽  
Art Methods ◽  
Mechanical Cleavage

Abstract Graphene exhibits a variety of unprecedented innate properties and has sparked great interest in both fundamental science and regarding prospective commercial applications. To meet the ever-increasing demand for high-quality graphene sheets, an industrial-scale, reliable, environmental-friendly, low-cost production process is required. However, large-scale production high quality graphene remains elusive. Here we demonstrate a scalable mechanical cleavage method for large-quantity production of high quality large-area and few-layer graphene sheets by introducing a millstone grinding process. The average thickness of the graphene sheets is around 5 nm. This procedure is simpler than the state-of-the-art methods that allows for scalable preparation of graphene dispersion in hundreds of litres by mechanical cleavage of graphite, and the yield is 30-40%. The size of the prepared graphene sheets can be tuneable from few micrometres to tens of micrometres by varying the dimension of raw graphite, which is larger than that produced by the state-of-the-art methods. Moreover, comparing to conductive agents, the conductivity of wafers containing graphene can be increased by one order of magnitude, suggesting a high potential of the prepared graphene sheets for the application as conductive agent in lithium battery cathodes. This allows the requirements of different sizes graphene sheets for industry applications in different fields.

A Groundwork Based Novel Routing Protocol for Vehicular Ad hoc Networks

2017 ◽  
Vol 7 (11) ◽  
pp. 121
Author(s):  
Amolkirat Singh ◽  
Guneet Saini
Keyword(s):  
Routing Protocol ◽  
Packet Loss ◽  
Secure Communication ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Road Traffic ◽  
Traditional Approach ◽  
Unexpected Events ◽  
The Road ◽  
On The Road

Many people lose their life and/or are injured due to accidents or unexpected events taking place on road networks. Besides traffic jams, these accidents generate a tremendous waste of time and fuel. Undoubtedly, if the vehicles are provided with timely and dynamic information related to road traffic conditions, any unexpected events or accidents, the safety and efficiency of the transportation system with respect to time, distance, fuel consumption and environmentally destructive emissions can be improved. In the field of computer and information science, Vehicular Ad hoc Network (VANET) have recently emerged as an effective tool for improving road safety through propagation of warning messages among the vehicles in the network about potential obstacles on the road ahead. VANET is a research area which is in more demand among the researchers, the automobile industries and scientists to discover about the loopholes and advantages of the vehicular networks so that efficient routing algorithms can be developed which can provide reliable and secure communication among the mobile nodes.In this paper, we propose a Groundwork Based Ad hoc On Demand Distance Vector Routing Protocol (GAODV) focus on how the Road Side Units (RSU’s) utilized in the architecture plays an important role for making the communication reliable. In the interval of finding the suitable path from source to destination the packet loss may occur and the delay also is counted if the required packet does not reach the specified destination on time. So to overcome delay, packet loss and to increase throughput GAODV approach is followed. The performance parameters in the GAODV comes out to be much better than computed in the traditional approach.

scholarly journals Multi-hop assortativities for network classification

2018 ◽  
Vol 7 (4) ◽  
pp. 603-622 ◽  
Author(s):  
Leonardo Gutiérrez-Gómez ◽  
Jean-Charles Delvenne
Keyword(s):  
Machine Learning ◽  
Scientific Collaboration ◽  
State Of The Art ◽  
Medical Engineering ◽  
Research Field ◽  
Classification Task ◽  
Collaboration Network ◽  
Structural Patterns ◽  
Art Methods

Abstract Several social, medical, engineering and biological challenges rely on discovering the functionality of networks from their structure and node metadata, when it is available. For example, in chemoinformatics one might want to detect whether a molecule is toxic based on structure and atomic types, or discover the research field of a scientific collaboration network. Existing techniques rely on counting or measuring structural patterns that are known to show large variations from network to network, such as the number of triangles, or the assortativity of node metadata. We introduce the concept of multi-hop assortativity, that captures the similarity of the nodes situated at the extremities of a randomly selected path of a given length. We show that multi-hop assortativity unifies various existing concepts and offers a versatile family of ‘fingerprints’ to characterize networks. These fingerprints allow in turn to recover the functionalities of a network, with the help of the machine learning toolbox. Our method is evaluated empirically on established social and chemoinformatic network benchmarks. Results reveal that our assortativity based features are competitive providing highly accurate results often outperforming state of the art methods for the network classification task.

scholarly journals Automatic Detection of Discrimination Actions from Social Images

Electronics ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 325
Author(s):  
Zhihao Wu ◽  
Baopeng Zhang ◽  
Tianchen Zhou ◽  
Yan Li ◽  
Jianping Fan
Keyword(s):  
Action Recognition ◽  
State Of The Art ◽  
Automatic Detection ◽  
Experimental Results ◽  
Practical Approach ◽  
Detection And Identification ◽  
Art Methods ◽  
Image Set ◽  
Social Images ◽  
Relationship Identification

In this paper, we developed a practical approach for automatic detection of discrimination actions from social images. Firstly, an image set is established, in which various discrimination actions and relations are manually labeled. To the best of our knowledge, this is the first work to create a dataset for discrimination action recognition and relationship identification. Secondly, a practical approach is developed to achieve automatic detection and identification of discrimination actions and relationships from social images. Thirdly, the task of relationship identification is seamlessly integrated with the task of discrimination action recognition into one single network called the Co-operative Visual Translation Embedding++ network (CVTransE++). We also compared our proposed method with numerous state-of-the-art methods, and our experimental results demonstrated that our proposed methods can significantly outperform state-of-the-art approaches.

scholarly journals A New Multi-Person Pose Estimation Method Using the Partitioned CenterPose Network

2021 ◽  
Vol 11 (9) ◽  
pp. 4241
Author(s):  
Jiahua Wu ◽  
Hyo Jong Lee
Keyword(s):  
Pose Estimation ◽  
Human Body ◽  
State Of The Art ◽  
Estimation Method ◽  
Bottom Up ◽  
Center Point ◽  
Novel Approach ◽  
Body Joints

In bottom-up multi-person pose estimation, grouping joint candidates into the appropriately structured corresponding instance of a person is challenging. In this paper, a new bottom-up method, the Partitioned CenterPose (PCP) Network, is proposed to better cluster the detected joints. To achieve this goal, we propose a novel approach called Partition Pose Representation (PPR) which integrates the instance of a person and its body joints based on joint offset. PPR leverages information about the center of the human body and the offsets between that center point and the positions of the body’s joints to encode human poses accurately. To enhance the relationships between body joints, we divide the human body into five parts, and then, we generate a sub-PPR for each part. Based on this PPR, the PCP Network can detect people and their body joints simultaneously, then group all body joints according to joint offset. Moreover, an improved l1 loss is designed to more accurately measure joint offset. Using the COCO keypoints and CrowdPose datasets for testing, it was found that the performance of the proposed method is on par with that of existing state-of-the-art bottom-up methods in terms of accuracy and speed.

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