Moving Object Research Articles

Moving Object Detection using Intelligent Spectaculars

Abstract: Moving Object detection systems are used to identify and locate objects in images or videos. When used spectacles, an object detection system can allow the user to see information about the objects in their field of view. This can be useful in a variety of applications, such as helping blind people navigate their environment, or providing augmented reality information to workers. Region-based Convolutional Neural Networks (RCNN) is a type of machine learning model that is commonly used for object detection. The RCNN model first uses a convolutional neural network (CNN) to extract features from the input image, and then applies a region proposal algorithm to identify potential object regions in the image. These regions are then fed into a second CNN, which classifies the regions as objects or background. The RCNN model has been shown to be effective at detecting a wide range of objects in images and videos.

Optimization of the Risk Functional to Control the Composition and Structure of a Heterogenous Grouping of Detection Sensors in Three-Dimensional Space

The steady growth in the scale and dynamics of the use of aerial weapons in the course of various conflicts necessitates the formulation and solution of the problems of building realistic systems to detect them. It should be noted that the priorities in the development of detection sensors is changing from solving problems to improve their characteristics to optimization and adaptability in controlling them. As an object, a heterogeneous grouping of sensors, which solves the problem of detecting a moving airborne object, is considered. The subject is the methodology for constructing control models for heterogeneous detection sensors. Based on the analysis of the antagonistic interaction of a heterogeneous grouping and airborne objects, as well as the processes of their functioning, a geometric approach to solve the problem of detecting a moving object (MO) is proposed, which uses an adapted and improved risk functional as one of the possible indicators for the further synthesis of the control algorithms. The practical effectiveness of the application of this functionality is substantiated and compared with other performance indicators through simulation modeling.

Smart Task Assistance in Mixed Reality for Astronauts.

Mixed reality (MR) registers virtual information and real objects and is an effective way to supplement astronaut training. Spatial anchors are generally used to perform virtual-real fusion in static scenes but cannot handle movable objects. To address this issue, we propose a smart task assistance method based on object detection and point cloud alignment. Specifically, both fixed and movable objects are detected automatically. In parallel, poses are estimated with no dependence on preset spatial position information. Firstly, YOLOv5s is used to detect the object and segment the point cloud of the corresponding structure, called the partial point cloud. Then, an iterative closest point (ICP) algorithm between the partial point cloud and the template point cloud is used to calculate the object's pose and execute the virtual-real fusion. The results demonstrate that the proposed method achieves automatic pose estimation for both fixed and movable objects without background information and preset spatial anchors. Most volunteers reported that our approach was practical, and it thus expands the application of astronaut training.

Legal Construction of Crypto Assets as Objects of Fiduciary Collateral

Crypto assets have become the commodities traded on the Futures Exchange. Based on the data from the Ministry of Trade, the number of crypto asset investors in Indonesia will reach 11 million people by the end of 2021. The high level of crypto investment and public interest in crypto as a digital asset provide excellent opportunities for Indonesia's digital industry and economic growth. This research will discuss the use of crypto assets as objects of fiduciary collaterals and the legal framework used as a legal basis for crypto assets subject to fiduciary collaterals. The research methodology is normative juridical applied using a comparative approach to the laws in Indonesia and Vietnam because the rules regarding crypto assets in Vietnam are clearer. The data collected were secondary data, and the they were analysed using qualitative data analysis. The results of the study show that crypto assets are intangible movable objects that have economic value and can be transferred due to an agreement through each user's account so that conceptually crypto assets can be used as fiduciary collateral objects. However, considering that crypto assets are digital currencies cannot be predicted, legal protection for creditors holding crypto asset collaterals is still weak. In addition to the absence of regulations that specifically regulate crypto assets that can be used as objects of fiduciary collateral, there are also difficulties in execution, so there is a need for a construction legal umbrella that regulates crypto assets to be used as fiduciary collateral objects.

A Dual-Input Moving Object Detection Method in Remote Sensing Image Sequences via Temporal Semantics

Moving object detection in remote sensing image sequences has been widely used in military and civilian fields. However, the complex background of remote sensing images and the small sizes of moving objects bring great difficulties for effective detection. To solve this problem, we propose a real-time moving object detection method for remote sensing image sequences. This method works by fusing the semantic information from a single image extracted by the object detection branch with the motion information of multiple frames extracted by the motion detection branch. Specifically, in the motion detection branch, we design a motion feature enhancement module (MFE) to improve the interframe motion information. Then, we design a Motion Information Extraction network (MIE) to extract motion information. Finally, the moving object information is directly output by fusing the motion and semantic information extracted by the object detection branch. Based on the experimental results of the two datasets, the proposed method achieves an accuracy rate of 93.21%, a recall rate of 92.72%, an average frame rate of 25.25 frames (fps), and a performance of 96.71% in terms of AP@0.5. The performance of the proposed method is better than that of other methods, and the overall detection effect is better; therefore, it meets the needs of the detection task.

Deep Learning-based Moving Object Segmentation: Recent Progress and Research Prospects

Moving object segmentation (MOS), aiming at segmenting moving objects from video frames, is an important and challenging task in computer vision and with various applications. With the development of deep learning (DL), MOS has also entered the era of deep models toward spatiotemporal feature learning. This paper aims to provide the latest review of recent DL-based MOS methods proposed during the past three years. Specifically, we present a more up-to-date categorization based on model characteristics, then compare and discuss each category from feature learning (FL), and model training and evaluation perspectives. For FL, the methods reviewed are divided into three types: spatial FL, temporal FL, and spatiotemporal FL, then analyzed from input and model architectures aspects, three input types, and four typical preprocessing subnetworks are summarized. In terms of training, we discuss ideas for enhancing model transferability. In terms of evaluation, based on a previous categorization of scene dependent evaluation and scene independent evaluation, and combined with whether used videos are recorded with static or moving cameras, we further provide four subdivided evaluation setups and analyze that of reviewed methods. We also show performance comparisons of some reviewed MOS methods and analyze the advantages and disadvantages of reviewed MOS methods in terms of technology. Finally, based on the above comparisons and discussions, we present research prospects and future directions.

A Novel Moving Object Detection Algorithm Based on Robust Image Feature Threshold Segmentation with Improved Optical Flow Estimation

The detection of moving objects in images is a crucial research objective; however, several challenges, such as low accuracy, background fixing or moving, ‘ghost’ issues, and warping, exist in its execution. The majority of approaches operate with a fixed camera. This study proposes a robust feature threshold moving object identification and segmentation method with enhanced optical flow estimation to overcome these challenges. Unlike most optical flow Otsu segmentation for fixed cameras, a background feature threshold segmentation technique based on a combination of the Horn–Schunck (HS) and Lucas–Kanade (LK) optical flow methods is presented in this paper. This approach aims to obtain the segmentation of moving objects. First, the HS and LK optical flows with the image pyramid are integrated to establish the high-precision and anti-interference optical flow estimation equation. Next, the Delaunay triangulation is used to solve the motion occlusion problem. Finally, the proposed robust feature threshold segmentation method is applied to the optical flow field to attract the moving object, which is the. extracted from the Harris feature and the image background affine transformation model. The technique uses morphological image processing to create the final moving target foreground area. Experimental results verified that this method successfully detected and segmented objects with high accuracy when the camera was either fixed or moving.

Cryptocurrency assets as a physical collateral in Indonesia

Cryptocurrency investment is currently expanding quickly on a global scale as well as in Indonesia. On the one hand, cryptocurrency can be used as a medium of exchange or a form of money, which represents the original purpose of cryptocurrency. On the other hand, it can also be used as a commodity or as digital assets, also known as crypto assets. Cryptocurrency is illegal to use as money in Indonesia, but it is legal to exchange it as an asset. This study explores the legal protections for holders of collateral against the loss of crypto assets as well as how crypto assets are governed by material guarantees in Indonesia. A conceptual and statutory approach, technical analysis, and a normative legal research methodology were applied in the study. The legal material was analyzed by using the content analysis approach, which involved examining the content and legality of the material gleaned from various laws and regulations by looking at the relevant legal precedents. The discussion results discover that crypto assets fall under the definition of "intangible movable objects" as defined in article 503 BW. In addition, crypto assets had material rights in the form of material guarantees in the form of a pledge and fiduciary guarantees, allowing the parties to carry out their agreements in good faith even in the event that the collateral object is lost. These disputes could be settled through either non-litigation or litigation.

Optimization of Bankruptcy Assets in the Form of Non-Fungible Token (NFT) by the Curator Based on Indonesian Bankruptcy Law

This research is a normative juridical study of non-fungible token (NFT) regarding the position of NFT in relation to positive law in Indonesia, legal certainty for bankrupt assets in the form of NFT and the efforts that can be made by curators in order to optimize bankruptcy assets in the form of NFT. The results of this study indicate that NFT has met the classification of immovable and indivisible movable objects. The provisions of Article 21, Article 98 and 101 Paragraph (1) of the Bankruptcy Law have provided legal certainty to curators and bankrupt creditors that NFT is a bankrupt asset that must be optimized by the curator to pay off the debts of debtors. There are 3 main obstacles by the curator in optimizing bankrupt assets in the form of NFT, in the process of registering NFT as bankrupt assets, the process of determining the best time to sell NFT and the method of selling NFT based on the Bankruptcy Law. Against these obstacles, the Bankruptcy Law and positive law have provided efforts that can be taken by curators in the context of optimizing bankrupt assets.

Control of Multi-Robots with Monocular Camera for Chasing a Moving Object Using Pseudo-Measurements

Control of Multi-Robots with Monocular Camera for Chasing a Moving Object Using Pseudo-Measurements

Detection of Moving Object Using Superpixel Fusion Network

Moving object detection is still a challenging task in complex scenes. The existing methods based on deep learning mainly use U-Nets and have achieved amazing results. However, they ignore the local continuity between pixels. In order to solve this problem, a method based on a superpixel fusion network (SF-Net) is proposed in this article. First, the median filter is used to extract the candidate foreground (called pixel features ) and the image sequence is segmented by superpixel. Then, the histogram features (called superpixel features ) of the candidate foreground superpixels are extracted. Next, the pixel features and the superpixel features are the inputs of SF-Net, respectively. Experiments show the effectiveness of SF-Net on 34 image sequences and the average F-measure reaches 0.84. SF-Net can remove more background noise and has stronger expression ability than a network with the same depth.

Detection of Moving Objects in Earth Observation Satellite Images

Moving objects have characteristic signatures in multi-spectral images made by Earth observation satellites that use push broom scanning. While the general concept is applicable to all satellites of this type, each satellite design has its own unique imaging system and requires unique methods to analyze the characteristic signatures. We assess the feasibility of detecting moving objects and measuring their velocities in one particular archive of satellite images made by Planet Labs Corporation with their constellation of SuperDove satellites. Planet Labs data presents a particular challenge in that the images in the archive are mosaics of individual exposures and therefore do not have unique time stamps. We explain how the timing information can be restored indirectly. Our results indicate that the movement of common transportation vehicles, airplanes, cars, and boats, can be detected and measured.

Akibat Hukum Akta Jaminan Fidusia yang Dibuat di Bawah Tangan dalam Kredit Motor

Purchasing motorbikes on credit involves third parties, namely consumer finance as financing lenders (creditors), while the party receiving the financing loan is called the debtor. The parties who bind themselves in the fiduciary guarantee deed under the hand do not have legal certainty for the parties, it is different from the fiduciary guarantee deed based on Law Number 42 of 1999 concerning Fiduciary Guarantees that have legal certainty. Fiduciary guarantees are guarantees for rights to movable or immovable objects other than land and buildings which are not included in mortgage rights. Through normative juridical research, research has been produced that the legal consequences of a fiduciary guarantee deed made privately are the frequent executions of unilateral interests, namely the creditor when there is a breach of contract made by the debtor. It is urgent to make a fiduciary guarantee deed which is notarized and registered at the fiduciary guarantee registration office to obtain a fiduciary certificate that has legal force.

Legal Problems The Implementation Of Credit Agreements With Fiduciary Guarantees

This look at targets to analyze the legal problems with the implementation of Credit Agreements, especially in relation to the credit using fiduciary guarantees as collateral. Financing institutions use Credit Agreements that are included in the Standard Agreement. Because credit is a business activity of financial institutions, in this case it is a bank, in order to achieve a national balance in distributing funds to the public. In carrying out its function, banks as financial institutions provide credit, therefore the provisions of the Guarantee Law are intended to help business activities both macro and micro, as well as create legal certainty for stakeholders. To achieve the goal of obtaining legal certainty regarding Credit Agreements with Fiduciary Guarantees, This study uses an empirical legal approach method, and the research specifications are descriptive analytical.This study produced a data, namely it was concluded that Fiduciary Guarantee is a form of guarantor by the debtor at his request, in order to guarantee the repayment of credit debts, movable objects become the object of guarantee in this study. The Supplementary Agreement or what is often referred to as the Accesoir of the Principal Credit Agreement can be guaranteed by the Fiduciary Guarantee, while the charge is made in the form of a notarized, by guaranteeing legal certainty so that it needs to be Register with the Trustee Registration Authority and apply for issuance of a Trustee Certificate to gain enforcement powers. The obstacle arises when defaulting by the debtor, with various causes and factors. Sometimes execution efforts are made to save credit that has been channeled by financing institutions, especially banks, but in practice there are many obstacles, including in executing the object of the guarantee that is not found, has changed hands or is controlled by others, so that execution in the form of auctioning fiduciary objects is difficult to do.

Communicating Missing Causal Information to Explain a Robot’s Past Behavior

Robots need to explain their behavior to gain trust. Existing research has focused on explaining a robot’s current behavior, yet it remains unknown yet challenging how to provide explanations of past actions in an environment that might change after a robot’s actions, leading to critical missing causal information due to moved objects. We conducted an experiment (N = 665) investigating how a robot could help participants infer the missing causal information by replaying the past behavior physically, using verbal explanations, and projecting visual information onto the environment. Participants watched videos of the robot replaying its completion of an integrated mobile kitting task. During the replay, the objects are already gone, so participants needed to infer where an object was picked, where a ground obstacle had been, and where the object was placed. Based on the results, we recommend combining physical replay with speech and projection indicators (Replay-Project-Say) to help infer all the missing causal information (picking, navigation, and placement) from the robot’s past actions. This condition had the best outcome in both task-based—effectiveness, efficiency, and confidence—and team-based metrics—workload and trust. If one’s focus is efficiency, then we recommend projection markers for navigation inferences and verbal markers for placing inferences.

Reconstruction of Fiduciary Collateral Execution Regulations Due to False Debtors Based on Justice Value

Execution of Fidusiary guarantee objects is an important issue in line with the growing development of granting credit with Fidusiary guarantees in credit agreements. The execution of Fidusiary guarantee objects is regulated in articles 29 to 34 of Law no. 42 concerning Fidusiary Guarantees, wherein the provision stipulates that if a debtor defaults, the execution of the object of Fidusiary guarantees can be carried out in two ways, namely through parate execution and private sales, but in practice, these provisions are difficult to implement properly. Based on these matters, it is necessary to study further when how a creditor can be said to have defaulted or defaulted, how is the process of executing Fidusiary guarantee objects in banking, and what are the obstacles that hinder carrying out the execution process of Fidusiary guarantees. The research method in writing this dissertation uses a juridical normative method with an explanatory research type, namely by examining and analyzing the relationship between the practice of executing Fidusiary guarantee objects in banking based on regulations related to this matter. In this study, secondary data was used, where to To obtain secondary data, the data collection tool used was a document study conducted using written data in the form of primary, secondary and tertiary legal materials, and then the data was analyzed qualitatively. Regulatory reconstruction of Article 15 paragraph (2) and paragraph (3) of the Fidusiary Security Act relating to the execution of Fidusiary guarantees in practice raises the creditor's arbitrariness when collecting, withdrawing Fidusiary collateral objects (movable objects) under the pretext of the debtor in breach of promise. Keywords: regulation, execution, agreement, default, value of justice. DOI: 10.7176/JLPG/129-03 Publication date: February 28 th 2023

The concept of limited mobile objects: civil-legal aspects

The right of ownership and the possibility of using his property for purposes that do not contradict the law, in particular, for entrepreneurial and other activities not prohibited by regulatory and legal acts has been guaranteed to every person. The prescriptions of the legislation regulating public and private relations, in their totality, have created legal limits of the turnover of objects of civil rights, which have been implemented on the main principles and legal principles. At the same time, the issue of limited turnover objects remains an understudied domestic science.
 Only the state, represented by its legislative body, is the subject authorized to determine which objects of civil rights are subject to restriction in civil turnover. At the same time, it should be taken into account that the definition of limited turnover objects is the quintessence of maintaining a balance between public and private interests, and therefore the establishment of special conditions for the turnover of a specific object must be considered and justified.
 In the article, it has been proposed to understand limited movable objects as an independent variety of objects of civil rights, which are capable of passing from one person to another, but due to their specific properties and/or special characteristics, combined with the need for protection from the state, can belong only to certain traffic participants or to be in civilian traffic only under the condition of obtaining a special permit. Also, in view of the provisions of the Civil Code of Ukraine, it seems incorrect to define the types of limited turnover objects at a normatively lower level than the law. Considering this, we support the approach according to which, in order to ensure the certainty of legal regulation, it is necessary to adopt a special law, which will establish a list of restricted objects or bodies that will determine their belonging to restricted circulation.

Semantic stereo visual SLAM toward outdoor dynamic environments based on ORB-SLAM2

PurposeThe prerequisite for most traditional visual simultaneous localization and mapping (V-SLAM) algorithms is that most objects in the environment should be static or in low-speed locomotion. These algorithms rely on geometric information of the environment and restrict the application scenarios with dynamic objects. Semantic segmentation can be used to extract deep features from images to identify dynamic objects in the real world. Therefore, V-SLAM fused with semantic information can reduce the influence from dynamic objects and achieve higher accuracy. This paper aims to present a new semantic stereo V-SLAM method toward outdoor dynamic environments for more accurate pose estimation.Design/methodology/approachFirst, the Deeplabv3+ semantic segmentation model is adopted to recognize semantic information about dynamic objects in the outdoor scenes. Second, an approach that combines prior knowledge to determine the dynamic hierarchy of moveable objects is proposed, which depends on the pixel movement between frames. Finally, a semantic stereo V-SLAM based on ORB-SLAM2 to calculate accurate trajectory in dynamic environments is presented, which selects corresponding feature points on static regions and eliminates useless feature points on dynamic regions.FindingsThe proposed method is successfully verified on the public data set KITTI and ZED2 self-collected data set in the real world. The proposed V-SLAM system can extract the semantic information and track feature points steadily in dynamic environments. Absolute pose error and relative pose error are used to evaluate the feasibility of the proposed method. Experimental results show significant improvements in root mean square error and standard deviation error on both the KITTI data set and an unmanned aerial vehicle. That indicates this method can be effectively applied to outdoor environments.Originality/valueThe main contribution of this study is that a new semantic stereo V-SLAM method is proposed with greater robustness and stability, which reduces the impact of moving objects in dynamic scenes.

Influence of reward and location on dogs’ behaviour toward an interactive artificial agent

Animal–robot interaction studies provide outstanding opportunities to understand the principles of social interactions. Here we investigated whether dogs’ behaviour toward a cooperative artificial agent (Unidentified Moving Object (UMO)) is influenced by receiving a reward directly from the agent, and by variability in the UMO’s location. In a problem-solving task, the UMO either helped dogs to obtain food (Direct Reward Group, DRG) or to fetch an object followed by an indirect reward from the owner/experimenter (Indirect Reward Group, IRG). During the Familiarization, the UMO either started from the same location or changed its starting location in all trials. In the Test phase, dogs faced the same task, but additionally a second, unfamiliar UMO was present. We found that both reward groups gazed at the UMO with decreasing latency during the Familiarization, with the IRG showing more gaze alternations between UMO and hiding location. Dogs showed no preference for either UMO in the Test phase but looked at the familiar UMO sooner if it had changed its location during the Familiarization. Thus, direct reward is not necessary to elicit elements of socially competent behavior in dogs, but variability in its motion may be important to improve the UMO’s animacy and promote flexible learning.

Perception of Size and Mass Relationships of Moving and Stationary Object in Collision Events in 10-to-11-Month-Old Infants.

Around 5.5-6.5 months of age, infants first attend to object size and perceive its mass cues in simple collision events. Infants attend to the size of the moving object and expect a greater displacement following a collision with a large object and stationary object, and lesser displacement following a collision with a small object and stationary object. It has been proposed that infants of 6-to-7 months of age can differentiate between sizes of moving objects but do not perceive the size and mass relationships in simple collision events. The present two investigations aimed to investigate whether infants 10-to-11 months of age (N = 16) could perceive this relationship (experiment 1) and the reverse of this relationship (experiment 2) utilising the looking time paradigm. The reverse of this relationship entailed the circumstances in which the moving object size was kept constant, but the stationary object size varied (small or large). Results from these experiments revealed that infants did not differ in their looking times for size congruent and size incongruent distances in both conditions. Infants did not look longer at the incongruent test events that violated expectation. For that reason, we conclude infants of 10-to-11 months of age were unable to perceive size and mass associations in collision events in either direction (moving object or stationary object size).