Aerial Perspective Research Articles

Epimeletic Behavior in Bottlenose Dolphins (Tursiops truncatus) in the South of Portugal: Underwater and Aerial Perspectives

Epimeletic Behavior in Bottlenose Dolphins (Tursiops truncatus) in the South of Portugal: Underwater and Aerial Perspectives

Design and fabrication of a stereo-video camera equipped unoccupied aerial vehicle for measuring sea turtles, sharks, and other marine fauna.

The recent commercialization of unoccupied aerial vehicles (UAVs) has facilitated their incorporation into a variety of ecological studies. While UAVs are able to provide accurate visual data of marine species from an aerial perspective, these devices have some limitations that make measuring marine animals below the surface challenging. Many marine organisms are often visible from the air, but are deeper in the water column, and current methods cannot measure animals below the surface. Here, we developed and tested a stereo-video camera (SVC) system that was mounted onto a commercially-available UAV. We used the SVC-UAV to conduct remote body-size measurements for two marine species: the green sea turtle (Chelonia mydas) and the nurse shark (Ginglymostoma cirratum). When comparing SVC measurements to those taken by hand, the SVC-UAV had a mean absolute error (MAE) of 4.44 cm (n = 6; mean percent error (MPE) = 10.6%) for green sea turtles and 7.16 cm absolute error (n = 1; PE = 3.6%) for the nurse shark. Using a linear model, we estimated the slope of the SVC versus hand measurements for green sea turtles to be 1.085 (±0.099 SE), and accounting for the standard error, a measurement bias was not apparent. Using model selection, based on a global model predicting MAE from animal distance to the SVC and body size, the top ranked model was the intercept-only model. This indicates that neither animal distance nor body size strongly influenced measurement error. Incorporating SVC systems into UAVs can allow for relatively accurate measurements of near surface-dwelling marine species. To our knowledge, there is no other stand-alone SVC for UAVs available that offers similar accuracy and utility.

‘Aircraft and pencraft’: Between tradition and modernity in arctic varsity exploration

This paper unpacks the material practices and narrative strategies surrounding the aerial work of the 1924 Oxford University Arctic Expedition to Spitsbergen (now Svalbard). Examining the fluid nature of British tropes of polar heroic masculinities, the paper illustrates the adaptability of such tropes in the face of technological change. Specifically, it demonstrates how aviation was mobilised to construct a masculinist explorer subject conceived as simultaneously traditional and modern at a time when the Heroic Era of British exploration was said to have subsided. Significantly, the 1924 expedition was organised largely by and for undergraduate explorers, many of whom saw polar travel as a rite of passage not unlike military service. Hence, the expedition narrative connects to a culture of undergraduate Arctic exploration emerging from Oxbridge during the 1920s. In tracing the 1924 air programme, the paper examines the tensions between polar heroics and new technologies of travel, the significance of nationalist rivalries and failed ambitions in negotiating the status of polar aviation, and problematises the separation of aerial and earth-bound perspectives on polar travel. Focusing on the labour dedicated to bringing aerial technology to the north, the corporeality of the aerial perspective, and iterations of the vertical reciprocity between ground and air, the paper draws out how aircraft was configured both as an instrument for dispassionate observation and as a legitimate vessel for passionate exploration, mirroring and adapting nineteenth century rhetoric of British polar heroics. It is suggested that understanding such historically rooted mechanisms and their adaptability to cultural and technological change remain relevant in terms of contextualising British imaginaries of the Arctic.

Capturing the Void: Michael Light’s Aerial Photographs of the American West

In 2017 and 2018, the California-based photographer Michael Light went to the Great Basin, allegedly one of the emptiest places left in the continental United States, in search of the void. He returned with striking and aesthetically pleasing images of a desert that is far from empty. Working collaboratively with his colleagues at Radius Books, Light realized the series and photobook Lake Lahontan / Lake Bonneville (2019). In this work, Light employs the unique combination of aerial perspective and photographic abstraction to capture images of the Great Basin that challenge our perception of empty spaces, the desert, and the American West. Light’s images emphasize the paradoxical effect of humans on the environment while leaving space for interpretation. The work opens the viewer to larger questions about the impact all humans have on the earth, inevitably prompting viewers to recognize their own role in the process.

Future landscape visualization using a city digital twin: integration of augmented reality and drones with implementation of 3D model-based occlusion handling

Abstract The integration of augmented reality and drones allows past and future landscapes to be visualized from an aerial perspective. However, these visualizations still suffer from the occlusion problem, where the three-dimensional (3D) virtual model displayed in the real world is in front of a real-world object. Currently, city digital twins are essential for the sustainable development of cities and the development of detailed 3D models of cities. By visualizing the city digital twin, augmented reality can facilitate the participation of nonexpert citizens in the decision-making process of urban design, but research examples are limited. Here, using detailed city 3D models, we develop a digital-twin approach to outdoor augmented reality with occlusion handling for both first-person and bird’s-eye views. In a verification experiment, the occlusion handling accuracy of the prototype system was measured to be about 0.8 using intersection over union. The frame rate of the entire prototype system was about 30 fps, and the delay between the controller and the augmented reality device was about 3 s. The internet-based system architecture was developed to integrate augmented reality and drone systems. Our system allows multiple stakeholders involved in building construction projects to observe aerial perspectives of those projects, both on-site and off-site via an internet browser, using augmented reality with occlusion handling.

A Naturalistic Study of Vehicle Acceleration and Deceleration at an Intersection

<div class="section abstract"><div class="htmlview paragraph">Approaching an intersection and braking to a stop, as well as accelerating from a stop, is a common occurrence in daily life. While the experience is routine, the actual rate of deceleration and acceleration has not been analyzed from an orthogonal aerial perspective. The aerial perspective provides video footage that allows for accurate planar motion tracking and does not influence the drivers’ actions in any way. This paper examines the behavior of drivers at two separate signal light controlled intersections to determine both the rate at which they slow down to a stop, and also the rate at which they accelerate through the intersection after a signal change. The paper will also address the acceleration rate differences of vehicles who are first to reach the intersection in comparison to those that are directly behind another vehicle, as well as the lag in reaction between vehicles as they begin to accelerate from a stop.</div></div>

SDWBF Algorithm: A Novel Pedestrian Detection Algorithm in the Aerial Scene

Due to the large amount of video data from UAV aerial photography and the small target size from the aerial perspective, pedestrian detection in drone videos remains a challenge. To detect objects in UAV images quickly and accurately, a small-sized pedestrian detection algorithm based on the weighted fusion of static and dynamic bounding boxes is proposed. First, a weighted filtration algorithm for redundant frames was applied using the inter-frame pixel difference algorithm cascading vision and structural similarity, which solved the redundancy of the UAV video data, thereby reducing the delay. Second, the pre-training and detector learning datasets were scale matched to address the feature representation loss caused by the scale mismatch between datasets. Finally, the static bounding extracted by YOLOv4 and the motion bounding boxes extracted by LiteFlowNet were subject to the weighted fusion algorithm to enhance the semantic information and solve the problem of missing and multiple detections in UAV object detection. The experimental results showed that the small object recognition method proposed in this paper enabled reaching an mAP of 70.91% and an IoU of 57.53%, which were 3.51% and 2.05% higher than the mainstream target detection algorithm.

Exhibition Review: Devour the Land: War and American Landscape Photography since 1970

Exhibition Review: <i>Devour the Land: War and American Landscape Photography since 1970</i>

High-performance panoramic annular lens design for real-time semantic segmentation on aerial imagery

As the visual perception window of the drone system, the lens provides great help for obtaining visual information, detection, and recognition. However, traditional lenses carried on drones cannot have characteristics of a large field of view (FoV), small size, and low weight at the same time. To meet the above requirements, we propose a panoramic annular lens (PAL) system with 4K high resolution, a large FoV of (30 deg to 100 deg) × 360 deg, an angular resolution of 12.2 mrad of aerial perspective, and great imaging performance. We equip a drone system with our designed PAL to collect panoramic image data at an altitude of 100 m from the track and field and obtain the first drone-perspective panoramic scene segmentation dataset Aerial-PASS, with annotated labels of track and field. We design an efficient deep architecture for aerial scene segmentation. Trained on Aerial-PASS, the yielded model accurately segments aerial images. Compared with the ERF-PAPNet and SwiftNet semantic segmentation networks, the network we adopted has higher recognition accuracy with the mean IoU greater than 86.30%, which provides an important reference for the drone system to monitor and identify specific targets in real-time in a large FoV.

The Effect of Interactive Cues on the Perception ofAngiographic Volumes in Virtual Reality

ABSTRACT In this paper, we evaluate the effect of depth cues on the perception of three-dimensional cerebral angiographic data in a virtual reality (VR) environment. Specifically, a user study was conducted to evaluate the effectiveness of shading, pseudo-chromadepth and aerial perspective, both with and without a dynamic component, where the volume rendering parameters are modified based on the motion of the VR controllers. The results of the study showed that the type of cue that is used has little impact on decision time or relative depth perception, contrary to what has been previously observed in related works using 2D displays. However, shading resulted in better spatial understanding of local vascular structures. In terms of the effect of the dynamic cues, although they resulted in worse depth perception, they also resulted in less head movement which may provide a more ergonomic and intuitive solution for data exploration. This work is a first step towards gaining a better understanding of the interplay between interactive perceptual rendering and the impact is on spatial understanding of volume rendered medical data within VR contexts.

Assessing Visual Preferences of the Local Public for Environmental Mitigation Measures of Hydropower Impacts—Does Point-of-View Location Make a Difference?

Hydropower is a highly appreciated climate-friendly source of energy production. However, it has non-negligible negative impacts on the environment and landscape aesthetics where the energy is produced, affecting the recreational interests of the public using the respective local river spaces. The preferences of the local public are increasingly assessed and involved in the planning of mitigation measures for impacted rivers. Aesthetic assessment methods using a common user perspective, i.e., an “on-the-ground” perspective, could potentially be improved by using an aerial perspective facilitated by modern drone technology. Studies on the compatibility of these two perspectives of assessment in terms of public preference elicitation are lacking so far. In river Nea, Norway, we conducted a quantitative analysis of the visual preferences of the local public for different environmental mitigation measures related to weirs, minimum flow, and recreational infrastructure using both perspectives. The results indicate that there exist significant differences in the preferences for scenarios based on the two different visual perspectives, and that a compatibility between them cannot be assumed and therefore requires further investigation. Finally, based on our study setup and previous experience, we outline and propose a standardized procedure for the visualization of mitigation measures as an input to environmental design projects where public perception is incorporated.

Topological Similarity-Based Multi-Target Correlation Localization for Aerial-Ground Systems

In this paper, an algorithm for solving the multi-target correlation and co-location problem of aerial-ground heterogeneous system is investigated. Aiming at the multi-target correlation problem, the fusion algorithm of visual axis correlation method and improved topological similarity correlation method are adopted in view of large parallax and inconsistent scale between the aerial and ground perspectives. First, the visual axis was preprocessed by the threshold method, so that the sparse targets were initially associated. Then, the improved topological similarity method was used to further associate dense targets with the relative position characteristics between targets. The shortcoming of dense target similarity with small difference was optimized by the improved topological similarity method. For the problem of co-location, combined with the multi-target correlation algorithm in this paper, the triangulation positioning model was used to complete the co-location of multiple targets. In the experimental part, simulation experiments and flight experiments were designed to verify the effectiveness of the algorithm. Experimental results show that the proposed algorithm can effectively achieve multi-target correlation positioning, and that the positioning accuracy is obviously better than other positioning methods.

Integration of visual landmark cues in spatial memory.

Over the past two decades, much research has been conducted to investigate whether humans are optimal when integrating sensory cues during spatial memory and navigational tasks. Although this work has consistently demonstrated optimal integration of visual cues (e.g., landmarks) with body-based cues (e.g., path integration) during human navigation, little work has investigated how cues of the same sensory type are integrated in spatial memory. A few recent studies have reported mixed results, with some showing very little benefit to having access to more than one landmark, and others showing that multiple landmarks can be optimally integrated in spatial memory. In the current study, we employed a combination of immersive and non-immersive virtual reality spatial memory tasks to test adult humans’ ability to integrate multiple landmark cues across six experiments. Our results showed that optimal integration of multiple landmark cues depends on the difficulty of the task, and that the presence of multiple landmarks can elicit an additional latent cue when estimating locations from a ground-level perspective, but not an aerial perspective.

Looking down: a model for visual route following in flying insects

Insect visual navigation is often assumed to depend on panoramic views of the horizon, and how these change as the animal moves. However, it is known that honey bees can visually navigate in flat, open meadows where visual information at the horizon is minimal, or would remain relatively constant across a wide range of positions. In this paper we hypothesise that these animals can navigate using view memories of the ground. We find that in natural scenes, low resolution views from an aerial perspective of ostensibly self-similar terrain (e.g. within a field of grass) provide surprisingly robust descriptors of precise spatial locations. We propose a new visual route following approach that makes use of transverse oscillations to centre a flight path along a sequence of learned views of the ground. We deploy this model on an autonomous quadcopter and demonstrate that it provides robust performance in the real world on journeys of up to 30 m. The success of our method is contingent on a robust view matching process which can evaluate the familiarity of a view with a degree of translational invariance. We show that a previously developed wavelet based bandpass orientated filter approach fits these requirements well, exhibiting double the catchment area of standard approaches. Using a realistic simulation package, we evaluate the robustness of our approach to variations in heading direction and aircraft height between inbound and outbound journeys. We also demonstrate that our approach can operate using a vision system with a biologically relevant visual acuity and viewing direction.

Image Preprocessing for Artistic Robotic Painting

Artistic robotic painting implies creating a picture on canvas according to a brushstroke map preliminarily computed from a source image. To make the painting look closer to the human artwork, the source image should be preprocessed to render the effects usually created by artists. In this paper, we consider three preprocessing effects: aerial perspective, gamut compression and brushstroke coherence. We propose an algorithm for aerial perspective amplification based on principles of light scattering using a depth map, an algorithm for gamut compression using nonlinear hue transformation and an algorithm for image gradient filtering for obtaining a well-coherent brushstroke map with a reduced number of brushstrokes, required for practical robotic painting. The described algorithms allow interactive image correction and make the final rendering look closer to a manually painted artwork. To illustrate our proposals, we render several test images on a computer and paint a monochromatic image on canvas with a painting robot.

Seamless integration of above- and under-canopy unmanned aerial vehicle laser scanning for forest investigation

BackgroundCurrent automated forest investigation is facing a dilemma over how to achieve high tree- and plot-level completeness while maintaining a high cost and labor efficiency. This study tackles the challenge by exploring a new concept that enables an efficient fusion of aerial and terrestrial perspectives for digitizing and characterizing individual trees in forests through an Unmanned Aerial Vehicle (UAV) that flies above and under canopies in a single operation. The advantage of such concept is that the aerial perspective from the above-canopy UAV and the terrestrial perspective from the under-canopy UAV can be seamlessly integrated in one flight, thus grants the access to simultaneous high completeness, high efficiency, and low cost.ResultsIn the experiment, an approximately 0.5 ha forest was covered in ca. 10 min from takeoff to landing. The GNSS-IMU based positioning supports a geometric accuracy of the produced point cloud that is equivalent to that of the mobile mapping systems, which leads to a 2–4 cm RMSE of the diameter at the breast height estimates, and a 4–7 cm RMSE of the stem curve estimates.ConclusionsResults of the experiment suggested that the integrated flight is capable of combining the high completeness of upper canopies from the above-canopy perspective and the high completeness of stems from the terrestrial perspective. Thus, it is a solution to combine the advantages of the terrestrial static, the mobile, and the above-canopy UAV observations, which is a promising step forward to achieve a fully autonomous in situ forest inventory. Future studies should be aimed to further improve the platform positioning, and to automatize the UAV operation.

Individual tree crown segmentation from airborne LiDAR data using a novel Gaussian filter and energy function minimization-based approach

Accurate segmentation of individual tree crowns (ITCs) from airborne light detection and ranging (LiDAR) data remains a challenge for forest inventories. Although many ITC segmentation methods have been developed to derive tree crown information from airborne LiDAR data, these algorithms contain uncertainty in processing false treetops because of foliage clumps and lateral branches, overlapping canopies without clear valley-shape areas, and sub-canopy crowns with neighbouring trees that obscure their shapes from an aerial perspective. Here, we propose an approach to crown segmentation using computer vision theories applied in different forest types. First, a dual Gaussian filter was designed with automated adaptive parameter assignment and a screening strategy for false treetops. This preserved the geometric characteristics of sub-canopy trees while eliminating false treetops. Second, anisotropic water expansion controlled by the energy function was applied for accurate crown segmentation. This utilized gradient information from the digital surface model and explored the morphological structures of tree crown boundaries as analogous to the maximal valley height difference from surrounding treetops. We demonstrate the generality of our approach in the subtropical forests within China. Our approach enhanced the detection rate of treetops and ITC segmentation relative to the marker-controlled watershed method, especially in complicated intersections of multiple crowns. A high performance was demonstrated for three pure Eucalyptus plots (a treetop detection rate r ≥ 0.95 and crown width estimation R2 ≥ 0.90 for canopy trees; r ≥ 0.85 and R2 ≥ 0.88 for sub-canopy trees) and three plots dominated by Chinese fir (r ≥ 0.95 and R2 ≥ 0.87 for canopy trees; r ≥ 0.79 and R2 ≥ 0.83 for sub-canopy trees). Finally, in a relatively complex forest park containing a wide range of tree species and sizes, a high performance was also achieved (r = 0.93 and R2 ≥ 0.85 for canopy trees; r = 0.70 and R2 ≥ 0.80 for sub-canopy trees). Our method demonstrates that methods inspired by the computer vision theory can improve on existing approaches, providing the potential for accurate crown segmentation even in mixed forests with complex structures

Quantifying Waterfowl Numbers: Comparison of Drone and Ground-Based Survey Methods for Surveying Waterfowl on Artificial Waterbodies

Drones are becoming a common method for surveying wildlife as they offer an aerial perspective of the landscape. For waterbirds in particular, drones can overcome challenges associated with surveying locations not accessible on foot. With the rapid uptake of drone technology for bird surveys, there is a need to compare and calibrate new technologies with existing survey methods. We compared waterfowl counts derived from ground- and drone-based survey methods. We sought to determine if group size and waterbody size influenced the difference between counts of non-nesting waterfowl and if detection of species varied between survey methods. Surveys of waterfowl were carried out at constructed irrigation dams and wastewater treatment ponds throughout the Riverina region of New South Wales (NSW), Australia. Data were analyzed using Bayesian multilevel models (BMLM) with weakly informative priors. Overall, drone-derived counts of waterfowl were greater (+36%) than ground counts using a spotting scope (β_ground= 0.64 [0.62–0.66], (R2 = 0.973)). Ground counts also tended to underestimate the size of groups. Waterbody size had an effect on comparative counts, with ground counts being proportionally less than drone counts (mean = 0.74). The number of species identified in each waterbody type was similar regardless of survey method. Drone-derived counts are more accurate compared to traditional ground counts, but drones do have some drawbacks including initial equipment costs and time-consuming image or photo processing. Future surveys should consider using drones for more accurately surveying waterbirds, especially when large groups of birds are present on larger waterbodies.

Routes and transects: Reading extended urbanization in alpine zones

Urbanization is rapidly extending to alpine zones across our planet. Many mountainous landscapes are now destinations for leisure and are being transformed by the fragmented development of infrastructure. What are the extended forms of urbanization in these mountains? How can we read the complex interplay of such forms under the pressure of tourism? Beyond reading from an aerial perspective, the author introduces an array of landscape-informed fieldwork methods based on travelling transects of multiscalar routes, represented through photography and cartography. The transects contribute to a more nuanced and holistic understanding of alpine landscapes, presented in the case study of Mount Gongga of the Hengduan Mountains. Included in global travel narratives of the twentieth century, this Chinese alpine zone has recently experienced a dramatic transformation, providing a territory for testing the methods and, furthermore, for raising a question: Could this landscape-informed perspective open up other ways of reading and strategies to adapt urbanization to alpine landscapes?

Aerial perspective for shaded relief

ABSTRACT Aerial perspective is an essential design principle for shaded relief that emphasizes high elevation terrain using strong luminance contrast and low elevations with low contrast. Aerial perspective results in a more expressive shaded relief and helps the reader to understand the structure of a landscape more easily. We introduce a simple yet effective method for adding aerial perspective to shaded relief that is easy to control by the mapmaker.