First-person View Research Articles

Cognitive Radar Waveform Selection for Low-Altitude Maneuvering-Target Tracking: A Robust Information-Aided Fusion Method

In this paper, we introduce an innovative interacting multiple-criterion selection (IMCS) idea to design the optimal radar waveform, aimingto reduce tracking error and enhance tracking performance. This method integrates the multiple-hypothesis tracking (MHT) and Rao–Blackwellized particle filter (RBPF) algorithms to tackle maneuvering First-Person-View (FPV) drones in a three-dimensional low-altitude cluttered environment. A complex hybrid model, combining linear and nonlinear states, is constructed to describe the high maneuverability of the target. Based on the interacting multiple model (IMM) framework, our proposed IMCS method employs several waveform selection criteria as models and determines the optimal criterion with the highest probability to select waveform parameters. The simulation results indicate that the MHT–RBPF algorithm, using the IMCS method for adaptive parameter selection, exhibits high accuracy and robustness in tracking a low-altitude maneuvering target, resulting in lower root mean square error (RMSE) compared with fixed- or single-waveform selection mechanisms.

METHOD OF RECOGNITION OF FPV-UAV RADIO SIGNALS FORMED ACCORDING TO CROSSFIRE AND EXPRESSLRS STANDARDS

Unmanned aerial vehicles (UAVs) with the First Person View (FPV) system are the most common type of attack UAVs used at the tactical level by the armed forces of the russian federation. Timely detection of facts of their using by the enemy and countering them are important tasks solved by units of the Ukrainian Defense Forces. An effective countermeasure way for FPV-UAVs is to create interference in their radio control channels frequency bands. To increase the radio suppression range, it is necessary to use interference matched in frequency and structure, the necessary condition for the formation of which is the presence of a priori information about the structure of the radio signal. Analysis of the available information on the construction of enemy FPV-UAVs shows that their radio control and telemetry channels are usually combined, have time division multiple access, the signals are formed according to CrossFire and ExpressLRS standards and have fixed sets of parameter values that can be used as features in recognition. The proposed FPV-UAV radio signal recognition technique is based on decision tree and minimum metric methods and uses a priori information on frequency, time and modulation parameters of radio signals. The combination of the two decision-making methods made it possible to reduce the computational complexity by eliminating operations for determining the parameters of radio signals that do not correspond to the decisions taken at the previous stages, and provides the possibility of adding new time parameters without changing the developed recognition technique. The method consists of a sequence of operations for estimation radio signal parameters, comparing them with known values, making decisions about the type of standard and command- telemetry radio line operation mode. Only one fragment with a duration of one frequency element is sufficient to recognize the FPV-UAV radio signal, which reduces the technical requirements for detection means in which the method can be used.

3D built virtual arctic environment increase vigor through connectedness in older people.

While the life expectancy of older people has increased significantly, this is often related to more long-term care in healthcare residences and nursing homes. Staying in these facilities can lead to a reduction in the sense of connection with others and the world around, as well as in vigor, with significant psychophysical repercussions in the long term. Although previous studies have shown that the virtual nature can benefit both, there are no significant studies that have tested its effect in generating these positive outcomes in the older population. Therefore, our study sought to investigate, in a sample of 53 older people in care at a nursing home or healthcare residence, the indirect effect of a 3D built virtual arctic environment (vs. a 3D built virtual urban environment) exposure in virtual reality on vigor through connectedness. Both the virtual scenarios were designed with a first-person view, with no translation around the environment and only in-situ rotation. Results highlighted that exposure to the 3D built virtual arctic environment leads to higher connectedness than the 3D built virtual urban environment, and this, in turn, leads to an increase in vigor. Findings were discussed based on the potential of adopting virtual nature in facilities to improve older people's sense of connectedness and, in turn, improve their well-being.

Visual augmentation of live-streaming images in virtual reality to enhance teleoperation of unmanned ground vehicles

First-person view (FPV) technology in virtual reality (VR) can offer in-situ environments in which teleoperators can manipulate unmanned ground vehicles (UGVs). However, non-experts and expert robot teleoperators still have trouble controlling robots remotely in various situations. For example, obstacles are not easy to avoid when teleoperating UGVs in dim, dangerous, and difficult-to-access areas with environmental obstacles, while unstable lighting can cause teleoperators to feel stressed. To support teleoperators’ ability to operate UGVs efficiently, we adopted construction yellow and black lines from our everyday life as a standard design space and customised the Sobel algorithm to develop VR-mediated teleoperations to enhance teleoperators’ performance. Our results show that our approach can improve user performance on avoidance tasks involving static and dynamic obstacles and reduce workload demands and simulator sickness. Our results also demonstrate that with other adjustment combinations (e.g., removing the original image from edge-enhanced images with a blue filter and yellow edges), we can reduce the effect of high-exposure performance in a dark environment on operation accuracy. Our present work can serve as a solid case for using VR to mediate and enhance teleoperation operations with a wider range of applications.

Algorithm for Precise Payload Drop From FPV Drone with Account of Wind Strength and Automatic Position Correction

The work is devoted to the development of an automatic system for dropping cargo from an first-person view drone. An analysis of approaches to the construction of this type of system was performed. It is proven that this problem has not been fully solved, which requires the development of new approaches. In order to increase accuracy, it is proposed to use mathematical models that describe the process of cargo unloading. Mathematical models are given that connect such variables as Height, wind speed, drone speed, cargo weight, cargo surface area, wind direction angle relative to the drone, air density. The use of the obtained mathematical models allows you to calculate the coordinates of the reset point. The developed approach was tested in real conditions. The obtained results showed a significant improvement in the accuracy of dropping the load in the presence of a constantly acting wind.

Segmentation of image from a first-person-view unmanned aerial vehicle based on a simple ant algorithm

The object of this study is the process of image segmentation from the First Person View (FPV) of an unmanned aerial vehicle (UAV). The main hypothesis of the study assumes that the use of a simple ant algorithm could ensure the necessary quality of the segmented image. The segmentation method, unlike the known ones, takes into account the number of ants in the image, weight, initial amount and evaporation rate of the pheromone, the "greediness" of the algorithm and provides: – preliminary selection of individual channels of the Red-Green-Blue (RGB) color space; – preliminary placement of ants according to the uniform law; – determining the routes of ants; – taking into account the attractiveness of the route for each ant; – change (adjustment) in the concentration of ant pheromones; – calculation of the probability of movement (transition) of the ant on the movement route; – determination of the objective function at the j-th iteration and its minimization; – determining the coordinates of the route of movement (movement) of ants; – verification of the fulfillment of the stop condition; – determination of the best routes found by ants; – calculation of the brightness of the pixels of the segmented image in each channel of the RGB color space; – further combining the results of channel segmentation. An experimental study of image segmentation from UAV FPV based on a simple ant algorithm was conducted. The specified object of interest on the segmented image has a certain structure, unevenness of the contours, and can be further used for decoding, categorization, etc. Unlike the object of interest, the background ("garbage" objects) in the segmented image do not have a stable structure and can be further filtered out. It has been established that the segmented image by the known method based on the gradient module has a low contrast value, there are gaps in the segmented pixels of the object of interest. A segmented image using a method based on a simple ant algorithm is free from that drawback.

The viewing perspective effect in learning from instructional videos: A replication and neuroimaging extension

BackgroundThe viewing perspective effect refers to the finding that students learn better from instructional videos recorded from first-person perspective than third-person perspective, but little is known about the neural mechanism underlying this effect. AimsThis study investigates the underlying neural mechanism of the viewing perspective effect. SamplesParticipants were 60 university students in Experiment 1, and 65 university students in Experiment 2. MethodsExperiment 1 replicated previous studies by using paper folding tasks (i.e., butterfly and four-leaf clover). Participants were randomly assigned to the first-person view group (i.e., watching videos recorded from a first-person view) or the third-person view group (i.e., watching videos recorded from a third-person view). Experiment 2 extended viewing perspective research by using neuroimaging methodology. Participants were randomly assigned to the two groups as in Experiment 1, but with fNIRS probes placed on each student's head. Participants watched the butterfly video (watching phase) and then performed the task (imitation phase). ResultsThere was superior performance on the butterfly task with a first-person view over a third-person view in both experiments, replicating the viewing perspective effect. There was higher cortical activation in the first-person view group in the right dlPFC during the watching phase, and higher cortical activation in third-person view group in the left IPC during the imitation phase. ConclusionsThis study replicates viewing perspective effect and investigates the underlying neural mechanism of the viewing perspective effect.

PilotAR: Streamlining Pilot Studies with OHMDs from Concept to Insight

Pilot studies in HCI research serve as a cost-effective approach to validate potential ideas and identify impactful findings before extensive studies. Yet, the additional requirements of AR/MR, such as multi-view observations and increased multitasking, make it challenging to conduct pilot studies effectively, hindering innovations in this field. Based on interviews with 12 AR/MR researchers, we identified the key challenges associated with conducting AR/MR pilot studies with Optical See-Through Head-Mounted Displays (OST-HMDs, OHMDs), including the inability to observe and record in-context user interactions, increased task load, and difficulties with in-context data analysis and discussion. To tackle these challenges, we introduce PilotAR, a desktop-based tool designed iteratively to enhance OHMD-based AR/MR pilot studies. PilotAR facilitates data collection via live first-person and third-person views, multi-modal annotations, and flexible wizarding interfaces. It also accommodates multi-experimenter settings, streamlines the study process with configurable workflows and shortcuts, records annotated data, and eases results sharing. Formative testing, conducted using three case studies, has highlighted the significant benefits of PilotAR, as well as its potential for further development and refinement.

Using Mixed Reality to Teach Medical Students Lumbar Punctures

BackgroundGaining familiarity with bedside procedures during medical school is essential for preparing medical students for intern year. However, this is often not a core component of undergraduate medical education, and students often feel unprepared to perform bedside procedures upon graduation from medical school. Extended reality technologies have rapidly developed in the past few years, become more accessible, and show great promise in education, most recently in healthcare. We aim to show the feasibility and usability of a mixed-reality lumbar puncture simulated experience. MethodsWe created the mixed-reality simulation by filming a procedure conducted by an expert on a lumbar puncture simulator from the first-person view. We performed a study to assess the feasibility and usability of mixed-reality lumbar puncture training compared with traditional faculty-led high-fidelity mannikin-based simulation training. Fourth-year medical students were randomly selected to participate in the mixed-reality lumbar puncture training. Students watched the virtual first-person teaching via a virtual reality headset while mimicking hand movements on a lumbar puncture mannikin. Faculty taught students in the traditional high-fidelity group in small groups before practicing on the high-fidelity manikin. Students in both groups then performed the procedure entirely with performance assessed via a standardized checklist. Number of attempts to achieve a predetermined minimum passing score were recorded, and students were also surveyed regarding their experience with both simulations. ResultsFifty-nine percent of students felt comfortable using mixed reality as a training modality with less than 6% having any prior extended reality experience. More than 55% felt the mixed-reality experience was as effective as the traditional high-fidelity simulation training. Many students (72%) desired more mixed-reality opportunities. In terms of performance, 58.8% of students in the mixed-reality group vs 65.5% in the traditional group completed the checklist in 1 attempt (P = .79). ConclusionsWe demonstrate that mixed reality is an acceptable and effective modality to train health care professionals in lumbar punctures with opportunities to further enhance the immersive learning experience.

Third-Person View Attention Prediction in Natural Scenarios With Weak Information Dependency and Human-Scene Interaction Mechanism

First-person view attention has been widely studied in computer science domain since 1990s while third-person view attention in natural scenarios begins to gain the intensive interest until 2015. This paper focuses on the problem of third-person view attention prediction in natural scenarios where a human freely performs daily activities without constraints. To handle the two insuffiencies of existing methods: (i) assuming some extra information (except for input images) are given in advance and (ii) ignoring the importance of human-scene interaction, this paper proposes a model with weak information dependency, which helps to alleviate annotation costs. In addition, a transformer-based human-scene interaction mechanism is proposed to explore the global and long-dependency contexts between the human and scene. The pipeline of the proposed model is firstly extracting human and scene features, then inferring human attention probability map by fusing human and scene features via a transformer-based network, and finally predicting human attention object based on human attention probability map and object detection. The experiments on two public datasets validate the effectiveness of our model.

IX Forum of Pediatric Surgeons of Russia

The traditional IX Forum of Pediatric Surgeons of Russia took place on November 9–11, 2023, at the Izmailovo Hotel, Moscow. The plenary session of the forum included the presentation of the S.D. Ternovsky Prize, “for his great contribution to the development of domestic pediatric surgery”, wherein Professor L.I. Budkevich gave an assembly speech “Combustiology of childhood — a first-person view” (online). Professor A.Yu. Razumovsky presented a report and historical documentary film dedicated to the 100th anniversary of the birth of Yuri F. Isakov during the plenary session. The report “Pediatric surgery of the Russian Federation. Figures and Facts” was delivered by Professor D.A. Morozov. The plenary session ended with a message from Professors E.V. Yudina and O.G. Mokrushina, “Antenatal diagnosis of congenital defects”. The video session “How I Do It” included 17 presentations with original medical technologies. The working meeting of the main freelance pediatric surgeons of the constituent entities of Russia and department heads of pediatric surgery was combined with a meeting of the specialized commission “Pediatric surgery” of the Ministry of Health of Russia and was chaired by D.A. Morozov and A.Yu. Razumovsky. The scientific program of the forum included symposia (14), round tables (4), a seminar, and a workshop. Overall, the scientific program included 169 reports, and 645 specialists participated in the forum in person. In total, 1,674 participants were registered at the forum. The total broadcast duration of the forum on the Internet was 49.5 hours. On the final day of the forum, a traditional competition of scientific research works of young scientists transpired. The IX Forum of Pediatric Surgeons of Russia was a scientific and practical event of a federal scale, showing, in an interactive format, the evolution and time frame of current problems of our specialty. The content of the reports and discussion results determined the vector of further scientific development and ways of introducing new organizational solutions and advanced medical technologies into clinical practice.

Perception of motion salience shapes the emergence of collective motions

Despite the profound implications of self-organization in animal groups for collective behaviors, understanding the fundamental principles and applying them to swarm robotics remains incomplete. Here we propose a heuristic measure of perception of motion salience (MS) to quantify relative motion changes of neighbors from first-person view. Leveraging three large bird-flocking datasets, we explore how this perception of MS relates to the structure of leader-follower (LF) relations, and further perform an individual-level correlation analysis between past perception of MS and future change rate of velocity consensus. We observe prevalence of the positive correlations in real flocks, which demonstrates that individuals will accelerate the convergence of velocity with neighbors who have higher MS. This empirical finding motivates us to introduce the concept of adaptive MS-based (AMS) interaction in swarm model. Finally, we implement AMS in a swarm of ~102 miniature robots. Swarm experiments show the significant advantage of AMS in enhancing self-organization of the swarm for smooth evacuations from confined environments.

A multimodal stepwise-coordinating framework for pedestrian trajectory prediction

Pedestrian trajectory prediction from the first-person view has still been considered one of the challenging problems in automatic driving due to the difficulty of understanding and predicting pedestrian actions. Observing that pedestrian motion naturally contains the repetitive pattern of the gait cycle and global intention information, we design a Multimodal Stepwise-Coordinating Network, namely MSCN, to sufficiently leverage the underlying human motion properties. Specifically, we first design a multimodal spatial-frequency encoder, which encodes the periodicity of pedestrian motion with a frequency-domain enhanced Transformer and other visual information with a spatial-domain Transformer. Then, we propose a stepwise-coordinating decoder structure, which leverages both local and global information in sequence decoding through a two-stage decoding process. After generating a coarse sequence from the stepwise trajectory predictor, we design a coordinator to aggregate the corresponding representations used to generate the coarse sequence. Subsequently, the coordinator learns to output a refined sequence through a knowledge distillation process based on the aggregated representations. In this way, MSCN can adequately capture the representations of short-term motion behaviors, thus modeling better long-term sequence prediction. Extensive experiments show that the proposed model can achieve significant improvements over state-of-the-art approaches on the PIE and JAAD datasets by 16.1% and 16.4% respectively.

Advanced Tactical Helmet for Military Use

Abstract: Advanced features on a tactical helmet designed for military use. Soldiers in today's military operations must have improved situational awareness, strong communication skills, and superior protection when fighting. A new generation of tactical helmets with enhanced features is required because the standard helmets now in use do not adequately fulfil these criteria. To improve army performance and survivability The helmet has several extra features in addition to its extensive ESP32 CAM for real-time data visualization, communication systems for seamless inter-squad communication, and improved ballistic protection materials. Among these characteristics include the incorporation of a helmet camera's First-Person-View (FPV) live video feed into a base station, along with the base station's face detection capabilities for enhanced identification. SolidWorks was used in the design process to produce a unique 3D-printed helmet, while ESP32 and ESP8266 were used to power a custom mainboard that effectively controlled the helmet's functions. this creative solution aims to significantly improve military operations, increase survivability, and ensure the safety of soldiers on the battlefield.

Teknologi Kendali Kamera Fpv 2 DOF Melalui Gesture Kepala Dengan Sensor IMU (Inertial Measurement Unit)

In taking videos or photos while in the air, there are currently very many tools or media that can be used and with the current technology that is very rapidly developing, especially in science, it can do everything easily. In the electronic field, a drone is a device that can fly and be controlled unmanned using a remote control. This object has a designation that is called a UAV (Unmanned Aerial Vehicle). This drone has a variety starting from the shape, size, different characters, and functions. FPV is one of the important parts of the 2DOF FPV (first person view) drone as a head gesture combined with parts such as nano arduino, Blueotooth HC-04, Servo, servo tilt up, IP camera, nano arduino must be connected to bluetooth on the cellphone, servo functions as moving right and left in accordance with the user's head gesture, servo tilt up functions as a gesture from top to bottom according to the gesture of the user and IP camera functions as video streaming, VR Glasses or commonly called Googles are connected using HC-04 bluetooth. According to the function in VR Glasses, it will bring up the sensitivity and movement value on the servo and servo tilt up and display the camera display on the IP camera.

Video saliency prediction for First-Person View UAV videos: Dataset and benchmark

Visual saliency prediction plays a crucial role in Unmanned Aerial Vehicle (UAV) video analysis tasks. In this paper, an eye-tracking dataset of the immersive viewing of videos captured from a First-Person View (FPV) of UAVs is developed, which consists of 200 video clips captured by DJI FPV drones, with a resolution of 4K QHD. The videos cover six different genres and fourteen unique scenes. To study human visual attention in watching FPV videos, fixation points are recorded using an eye tracker integrated into a VR headset. Based on the dataset, a simple yet effective FPV UAV video Saliency prediction model (FUAVSal) is proposed as a baseline, considering spatial–temporal feature, camera motion information and FPV prior. To establish benchmarks for saliency prediction in immersive FPV UAV video viewing, sixteen computational models are evaluated on this dataset. Detailed quantitative and qualitative comparisons are provided. The developed dataset and benchmarks aim to facilitate research on visual saliency prediction for First-Person View UAV videos.

A Novel Obstacle Traversal Method for Multiple Robotic Fish Based on Cross-Modal Variational Autoencoders and Imitation Learning.

Precision control of multiple robotic fish visual navigation in complex underwater environments has long been a challenging issue in the field of underwater robotics. To address this problem, this paper proposes a multi-robot fish obstacle traversal technique based on the combination of cross-modal variational autoencoder (CM-VAE) and imitation learning. Firstly, the overall framework of the robotic fish control system is introduced, where the first-person view of the robotic fish is encoded into a low-dimensional latent space using CM-VAE, and then different latent features in the space are mapped to the velocity commands of the robotic fish through imitation learning. Finally, to validate the effectiveness of the proposed method, experiments are conducted on linear, S-shaped, and circular gate frame trajectories with both single and multiple robotic fish. Analysis reveals that the visual navigation method proposed in this paper can stably traverse various types of gate frame trajectories. Compared to end-to-end learning and purely unsupervised image reconstruction, the proposed control strategy demonstrates superior performance, offering a new solution for the intelligent navigation of robotic fish in complex environments.

IoT Based Drone Control

The integration of drones into various sectors has sparked a technological revolution, reshaping industries and redefining possibilities. This abstract delves into the multifaceted dimensions of drones, examining their evolution, applications, challenges, and future prospects. From aerial photography to disaster relief, drones have transcended traditional boundaries, fostering innovation and efficiency. However, ethical dilemmas, regulatory hurdles, and security concerns loom large, necessitating a balanced approach towards their deployment. As drones continue to soar to new heights, understanding their abstract impact on society becomes imperative for navigating the complexities of the modern technological landscape. Keywords: Some key words associated with drones are: ➢ UAV (Unmanned Aerial Vehicle) ➢ Quadcopter ➢ Remote-controlled aircraft ➢ Multirotor ➢ GPS navigation ➢ FPV (First Person View) ➢ Autopilot ➢ Payload ➢ Gimbal ➢ Telemetry

Development of a solar powered multirotor micro aerial vehicle

Rotary-wing aerial vehicles offer manoeuvrability and vertical take-off and landing (VTOL) advantages over fixed-wing systems. Rotary-wing systems do however have comparatively higher energy demands and consequently shorter flight times and therefore a greater energy dependence over their fixed-wing counterparts. Advances in photovoltaic technologies have resulted in significant increases in the specific power (power-to-weight-ratio) of solar cells enabling the design of solar-powered rotary-wing aircraft, and now micro-sized variants. The micro aerial vehicle (MAV) presented, the Micro Solarcopter, is a 0.15 m ×\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ imes$$\\end{document} 0.15 m ×\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ imes$$\\end{document} 0.02 m solar-rechargeable radio-controlled aircraft. The 0.071 kg aircraft can fly for an average time of 3.5 min, recharge in approximately 68 min under 1000 W/m2 irradiance at 25 °C and can hibernate for 38 days without sunlight. The paper explores the use of commercially available photovoltaic cells for the purpose of increasing the energy autonomy of multi-rotor MAVs, by enabling them to stay out in the field without returning to base for charging. A working prototype has been presented which incorporates a battery management system, automatic power on and off, low-power sleep mode, and first-person-view (FPV) camera.

Coordination of gaze and action during high-speed steering and obstacle avoidance.

When humans navigate through complex environments, they coordinate gaze and steering to sample the visual information needed to guide movement. Gaze and steering behavior have been extensively studied in the context of automobile driving along a winding road, leading to accounts of movement along well-defined paths over flat, obstacle-free surfaces. However, humans are also capable of visually guiding self-motion in environments that are cluttered with obstacles and lack an explicit path. An extreme example of such behavior occurs during first-person view drone racing, in which pilots maneuver at high speeds through a dense forest. In this study, we explored the gaze and steering behavior of skilled drone pilots. Subjects guided a simulated quadcopter along a racecourse embedded within a custom-designed forest-like virtual environment. The environment was viewed through a head-mounted display equipped with an eye tracker to record gaze behavior. In two experiments, subjects performed the task in multiple conditions that varied in terms of the presence of obstacles (trees), waypoints (hoops to fly through), and a path to follow. Subjects often looked in the general direction of things that they wanted to steer toward, but gaze fell on nearby objects and surfaces more often than on the actual path or hoops. Nevertheless, subjects were able to perform the task successfully, steering at high speeds while remaining on the path, passing through hoops, and avoiding collisions. In conditions that contained hoops, subjects adapted how they approached the most immediate hoop in anticipation of the position of the subsequent hoop. Taken together, these findings challenge existing models of steering that assume that steering is tightly coupled to where actors look. We consider the study's broader implications as well as limitations, including the focus on a small sample of highly skilled subjects and inherent noise in measurement of gaze direction.