Object Mapping Research Articles

Identification and mapping of objects targeted for surveillance and their role as risk factors for brucellosis in livestock farms in Kazakhstan

Identification and mapping of objects targeted for surveillance and their role as risk factors for brucellosis in livestock farms in Kazakhstan

Vehicle drivability evaluation based on PCA-SSA-XGBoost

In order to improve the efficiency and quality of vehicle drivability evaluation, a drivability evaluation model based on principal component analysis, extreme gradient boosting tree and sparrow optimization algorithm is proposed. In this paper, the power upshift of DCT vehicle is taken as a typical working condition, and 18 objective evaluation indicators under the power upshift working condition are studied and defined. The objective evaluation indicators are simplified by principal component analysis, their redundancy and blockiness are reduced, and the model input samples are optimized. The extreme gradient boosting tree model is trained to predict the subjective score of drivability, and the sparrow algorithm is used to optimize the core hyperparameters of the extreme gradient boosting tree to improve the accuracy and stability of the model. Road tests show that after the objective evaluation indicators are simplified by principal component analysis, the model evaluation accuracy reaches 97%, which is better than BPNN ( 90%), SVM ( 91%), ELM ( 92%) and SSA-XGBoost ( 95%). It is proved that the accuracy and stability of the proposed PCA-SSA-XGBoost model are better than other models, and it can complete the drivability evaluation more effectively. The evaluation model can be transferred and applied to other driving conditions, and has application value in solving the subjective and objective mapping problem in drivability evaluation.

Towards advanced sustainable criteria for choosing the best site for collecting solar energy in cities using multi-criteria GIS

Solar energy has become a prominent and crucial source of clean energy due to the increasing global demand for electricity. There is a prevailing global trend towards the construction of solar farms as a means of energy generation. This study aims to assess multiple criteria encompassing urban, environmental, and social aspects in order to ascertain the optimal site for constructing solar farms. The evaluation primarily focuses on characteristics such as topography, solar radiation, accessibility, land use, and proximity to roads and power stations. In order to acquire the necessary spatial fit model, the data was evaluated utilizing a Geographic Information System (GIS) program, and the criteria were subsequently consolidated into an integrated geographic information system. A comprehensive review of the existing body of literature reveals that environmental factors, specifically solar radiation and aspect, play a crucial role in determining the suitable places for the establishment of solar energy collection projects (Merrouni et al. in Energy Procedia 49:2270-2279, 2013; McKinney in J Student Res Environ Sci Appalac 4:1-14, 2014). Furthermore, other analysis factors such as proximity to built-up regions, closeness to power lines, and proximity to roadways are taken into account (Hott et al. in GIS-based Spatial Analysis For LargeScale Solar Power And Transmission Line Issues: Case Study of Wyoming, U.S. In: Proceedings of the 41st American Solar Energy Society Meeting, 2012; Effat in Int J Adv Remote Sens GIS 2:205-220, 2013). These criteria have an impact on the cost of solar farms. The objective of this study was to assess several aspects influencing the selection of an optimal location for a solar energy farm, taking into consideration the aforementioned criteria. The study was carried out in New Aswan city, utilizing data obtained from the Urban Planning Authority within the Ministry of Housing and Urban Development, as well as the New Aswan City AuthorityI generated cartographic representations and compiled quantitative data, which informed our selection of places that met the established criteria through the utilization of a Geographic Information System (GIS) software. Upon the conclusion of the study, numerous locations that satisfied the established criteria were selected. The present study focuses on regions with high capacity, and the findings are depicted in the form of spatial and objective maps. One of the primary benefits associated with the utilization of this methodology lies in its versatility, as it can be implemented across several domains. Furthermore, a straightforward adjustment of the criteria facilitates its application in the selection of optimal locations for wind farms.

AR/VR assisted integrated framework of autonomous disassembly system for industrial products

An immersive Augmented Reality (AR) technology enhances productivity and flexibility in manufacturing by providing real-time instructions within workers’ field of view, aiding in complex tasks. According to cognitive load and attention-based theories, AR guidance can reduce cognitive strain, enhancing task performance. The affordance of AR in industrial processes like assembly or disassembly for repair/maintenance has been exploited broadly. However, the prevailing studies on automated user interfaces for AR instruction development, specifically virtual scene creation and target generation for object mapping rendering, still need to be explored. Notably, production industries currently rely on outsourcing skilled professionals to create AR overlaying instructions using manufacturer input. However, the exactness of the disassembly repository is substantial to avoid defects in AR guidance particulars. This underscores the significance of generalized automated AR instruction development and emphasizes the demands for further research. In this work, the autonomous AR-integrated framework is developed for the disassembly context, empowering manufacturers to acquire desired outcomes across various modules. These modules include the validation of the manual user disassembly sequence repository during the prefatory phase of AR instruction creation and the provision of Disassembly Sequence Planning (DSP) input. Additionally, the framework supports the simulation/rendering of disassembly efforts in a virtual platform and the generation of rendering virtual display scenes for appropriate AR-guided object mapping. Furthermore, it enables the generation of essential model targets for registering the AR scenes. Subsequently, the extracted repositories (virtual scenes and model targets) are input into the Unity AR tool to create AR mapping guidance for disassembly operations. The performance of the autonomous disassembly module is evaluated through three case studies with different AR visualizations. Furthermore, the potential of the proposed framework is exploited by extracting feedback from experts regarding flexibility, compatibility, completion time, and cognitive level.

Saliency and edge features-guided end-to-end network for salient object detection

The rapid development of the Vision Transformer backbones has enabled the capture of feature information with global dependencies, leading to excellent performance in salient object detection tasks. However, it fails to adequately emphasize fine local features of edges, resulting in coarse and blurry edges in the final output. Therefore, this paper proposes a set prediction method for salient object detection. The approach enables the model to simultaneously consider both saliency (salient object) and edge features, achieving an end-to-end edge feature fusion. There is no need to design multiple complex branch structures and multiple training as with other methods. The model integrates random edge neighborhood sampling to enhance the recognition accuracy of local edge features in images. This approach addresses the weak perception of local features by Transformers and the issue encountered during actual training, where edge pixels typically occupy a much smaller proportion of the image compared to the background, resulting in insufficient learning of edge features by the model. The proposed end-to-end model in this paper fuses multiple features, including edge and salient objects. They are extracted within a unified framework while simultaneously outputting edge and salient object maps. Experimental results on six public datasets show that the proposed method significantly improves model performance benchmarks for detecting salient objects.

Специализированные топографические карты: становление, тенденции развития научного направления, технология создания

The prerequisites for dividing topographic maps and plans into basic and specialized ones are highlighted. The trends of specialized maps improvement as a scientific direction of topographic mapping influenced by accumulated experience of production work and scientific research were established. Increasing relevance and demand for making specialized maps of environment-forming objects with great natural and ecological potential is shown. The concept of 'type of specialized maps' is substantiated; it determined the structure and sequence of map-making technological stages. A technology for mapping environmental protection is proposed using the example of wetlands with unique biospheric functions. Its specific features at different stages of the process are revealed

A RBI Mapping Geographic Information System in Pangkep Regency Using ArcGis Online

The Indonesian Medan Map (RBI) is a topographic map that displays several natural and man-made elements in the territory of the Republic of Indonesia, especially in Pangkep Regency. The purpose of this study is to map sixteen RBI objects, namely Hospitals, Education, Industry, Health Centers, PLN Offices, Package Delivery Offices, Worship Facilities, Government, Ports, Post Offices, Gas Stations, Rivers, Dams, Roads, Irrigation, and Settlements. Use the ArcGIS Online app. This mapping is useful for providing information about the spatial data of objects and topographic maps. The method used is a survey by determining the coordinate points of each object. Furthermore, coordinate points are used as data input in ArcGIS applications. Primary data collection is carried out by direct observation of objects or places. Secondary data collection includes Quickbird Citra Pangkep Regency, as well as the Indonesian Medan Map (RBI). Data analysis was carried out in a descriptive manner. Based on the results of object mapping in Pangkep Regency, there are sixteen RBI objects, including: three health service objects, one education object, four transportation objects, five construction work service objects, one government object, one housing object and one worship object object. Sixteen RBI objects are spread throughout Pangkep district.

Calculation of the main operational characteristics of a tethered high-altitude ship-based system

Objectives. Currently, UAVs are actively used in many military and civilian fields such as object surveillance, telecommunications, radar, photography, video recording, and mapping, etc. The main disadvantage of autonomous UAVs is their limited operating time. The long-term operation of UAVs on ships can be ensured by tethered high-altitude systems in which the power supply of engines and equipment is provided from the onboard energy source through a thin cable tether. This paper aims to select and justify the appearance of such system, as well as to calculate the required performance characteristics.Methods. The study used methods of systemic and functional analysis of tethered system parameters, as well as methods and models of the theory of relations and measurement.Results. The issues of design and implementation of new generation tethered high-altitude ship-based systems were considered. A rational type of aerodynamic design for unmanned aerial vehicles was determined based on existing tethered platforms. The optimal architecture of the tethered system was defined and justified. The paper presents the appearance and solution for placement onboard the ship, and describes its operation. The main initial parameters for designing high-altitude systems such as take-off weight, optimal lift altitude, maximum power required for operation, structure of the energy transfer system, as well as deployment and lift time to the design altitude were selected and calculated.Conclusions. The methodology for calculating the necessary characteristics described in the paper can be used for developing and evaluating tethered high-altitude systems. These systems are capable of performing a wide range of tasks, without requiring a separate storage and launch location, which is especially important in the ship environment. The system presented herein possesses significant advantages over well-known analogues.

Production of maps for bearing capacity of the shallow foundation in Baghdad city using SPTs and MATLAB software

Abstract The standard penetration tests are considered one of the most important tests to determine the bearing capacity of the soil. In this research, a set of objective maps and equations were produced to estimate the bearing capacity of shallow foundations based on the results of SPTs conducted in Baghdad Governorate. The work includes drilling 213 wells 10 meters deep below the surface of the earth, and conducting three standard penetration tests (SPT) on each well at depths of 1.5, 6 and 9 m. The bearing capacity of the shallow foundations in the city of Baghdad was determined using the MATLAB program after the SPT values were corrected. Then several polynomial equations with multi-order interpolation are proposed to estimate the bearing capacity of the foundation, but the first-order polynomial equation is considered simpler and straightforward. Moreover, the root mean square error (RMSE) of all the proposed polynomial equations is almost the same. Thematic maps show the difference in the carrying capacity of shallow foundations across the total ground of Baghdad Governorate with respect to different depths. Then, a comparison was made between the calculated and estimated values of the foundation’s bearing capacity, where the results showed a discrepancy of 30% at a confidence level of 95%.

Optimization-based approach for high-fidelity phase retrieval from sparse interferometric data: implications for industry and biological research

Optical profilometers provide a non-contact, non-destructive method for swiftly profiling 3D surfaces. White light interferometers, often used for this purpose, employ a 5-phase shifting technique for precise phase maps. However, capturing multiple frames introduces mechanical movement, which impedes imaging of dynamic objects. White light’s low spatial-temporal coherence mitigates speckles and spurious fringes while offering high axial resolution. Creating a high fringe density interferogram with low-coherence light is challenging. Introducing a tilt angle in the interferometer can increase the fringe density, which is still insufficient for phase map retrieval using the single-shot Fourier transform method. We propose an adaptive optimization framework to recover phase maps from single low fringe density interferograms. This method iteratively extracts reference beam information, eliminating mechanical movement and enhancing system stability while reducing costs and system bulkiness. The simulation and experimental results on a step-phase object (etched on silicon) and biological MG63 osteosarcoma cells validate the efficacy of a single-shot optimization scheme. For comparison, the phase maps of the same objects were obtained using the single-shot Fourier transform and multi-shot 5-phase shifted methods. The single-shot optimization technique shows efficient performance, yielding phase maps with reasonable accuracy, potentially replacing the 5-phase shifting technique in industrial and biological diagnostics.

The natural ordering cone of a polyhedral convex set-valued objective mapping

ABSTRACT For a given polyhedral convex set-valued mapping we define a polyhedral convex cone which we call the natural ordering cone. We show that the solution behaviour of a polyhedral convex set optimization problem can be characterized by this cone. Under appropriate assumptions, the natural ordering cone is proven to be the smallest ordering cone which makes a polyhedral convex set optimization problem solvable.

The possibilities of using historical data on Tambov church monuments of the late 18th – first half of the 19th century in the development of an interactive map

Importance. A number of factors are considered: the possibility of providing relevant historical information to a wide audience, the use of modern technologies for analyzing and distributing historical information, and the significant interest of historians in working within the framework of the methodology used. The purpose of the study is to offer a resource for popularizing the church history of the region. The main sources are used in the work are plans of the city of Tambov and documents from the funds of the Tambov City Duma (16) and the Mezhevaya Chancellery (29) of the State Archive of the Tambov Region, some reference and visual materials, as well as a view of the city of Tambov in 1799.Research Methods. Both classical historical methods and the methodology of historical informatics are used.Results and Discussion. The relevance of modern information technologies use in scientific and educational activities is substantiated. A historiographical analysis of the problem has been carried out, which relates to the theoretical part of the study. The problems associateы with the localization of lost objects on modern maps and their solutions are described, which can be attributed to the practical part. Variants of references of the church history objects of Tambov city for an interactive map of the church history objects of Tambov at the end of the 18th – first half of the 19th century are proposed for consideration. The process of collecting and systematizing information for the formation of historical references of ancient religious buildings in Tambov: the Znamenskaya Church, the Church in the name of the Great Martyr Barbara and the Church of the Life-Giving Trinity is described.Conclusion. The main result of the study is the images demonstration of attaching cartographic, visual and descriptive data on the history of specific monuments of church history to maps.

Enhancing groundwater potential zone mapping with a hybrid analytical method: The case of semiarid basin

Groundwater resource management is a critical component of sustainable water use, necessitating accurate and nuanced mapping of groundwater potential zones. This study analyzed the groundwater potential of Algeria's 43,750 km2 Chelif Basin (more than 17% of the area of Northern Algeria) using a combination of both subjective and objective mapping techniques. The adopted approaches encompass the benchmark analytical Fuzzy Analytic Hierarchy Process (Fuzzy-AHP) and the DEcision MAking Trial and Evaluation Laboratory (DEMATEL) methodologies to quantify interdependencies of criteria related to groundwater potential. The analysis focused on ten criteria related to groundwater potential, including core moisture availability and key hydrological factors like distance to river, topographic wetness index, and hydrological soils. Fuzzy-AHP achieved slightly higher groundwater prospecting accuracy (AUC = 0.730) than classic AHP (0.716), with benchmarking against 15 related studies indicating robust performance. Instead of the most commonly used criteria in groundwater literature such as lineament, stream order, recharge rate, and drainage density, this study employed alternative factors to challenge and validate the efficacy of the proposed methodology. The decision to omit certain criteria facilitated a more focused and manageable analysis, yet still delivered a robust evaluation of groundwater potential in the studied area. Moreover, this approach underscores the adaptability of the proposed methodology to accommodate varying sets of criteria, tailored according to the availability of data and specific research objectives. Additionally, the DEMATEL evaluation reveals new insights into subtle prioritization divergences, specifically between domain specialist opinions and analytical assessments of the criteria. The integration of fuzzy logic and causal relationship mapping through DEMATEL provides a comprehensive and robust foundation for groundwater potential modeling.

Higher-order [formula omitted]-cone arcwisely connectedness in optimization problems associated with difference of set-valued maps

In this paper, an optimization problem (DP) is studied where the objective maps and the constraints are the difference of set-valued maps (abbreviated as SVMs). The higher-order σ-cone arcwise connectedness is described as an entirely new type of generalized higher-order arcwise connectedness for set-valued optimization problems. Under the higher-order contingent epiderivative and higher-order σ-cone arcwise connectedness suppositions, the higher-order sufficient Karush–Kuhn–Tucker (KKT) optimality requirements are demonstrated for the problem (DP). The higher-order Wolfe (WD) form of duality is investigated and the corresponding higher-order weak, strong, and converse theorems of duality are established between the primary (DP) and the corresponding dual problem by employing the higher-order σ-cone arcwise connectedness supposition. In order to demonstrate that higher-order σ-cone arcwise connectedness is more generalized than higher-order cone arcwise connectedness, an example is also constructed. As a special case, the results coincide with the existing ones available in the literature.

The Effects of Passage Through Vaccine Vial Septa on Needle Sharpness

Veterinarians anecdotally report changing needles before injection after drawing up a vaccine due to concerns for needle dulling. However, there is little information on the impact on needles during passage through vial septa, and the CDC does not recommend this practice. Sharps are considered medical waste and their disposal incurs regulatory burden while recapping a needle to remove it represents a hazard to veterinary personnel. Due to the large volume of vaccines administered in shelters, the cost to dispose and repurchase needles can be high. The aim of this study was to determine whether needles commonly used by veterinarians dull after passage through vial septa. A survey to determine the most common brands and gauges of needles, as well as needle-changing practices, was promoted to veterinarians and staff via social media from 5/5-5/12/23 (IRBAZ-5222). A Wagner FDIX ForceOne force gauge was used to measure peak force required to penetrate 0.020” thick Abrasion-Resistance Polyurethane Rubber (ISO 7864) for new needles, needles passed through 1 vial septum, and needles passed through 2 via septa (0, 1, 2) across 3 different brands (a, b, c) and 4 sizes (20, 22, 25 G) of single-use veterinary hypodermic needles. Needle tip and surfaces were visualized via 3D infinite focus microscopy (Bruker Alicona InfiniteFocusSL) with a 5XAX objective and subsequent deviation maps were created in Zeiss Inspect Professional (formerly GOM) to facilitate defect identification. Multivariable linear regression was used to determine the association between peak force and number of passages through a vaccine vial septum while controlling for needle brand, gauge, and vaccine vial penetration force (VVPF) and logistic regression to determine associations between gross defects and brand, gauge, and VVPF. Of the 482 survey respondents, 76% reported changing needles used to draw up a vaccine, primarily due to concerns about needle dulling. The peak force through a standard material was measured for 330 needles. The mean VVPF through the first septum was 2.1±0.7 N (range 0.4-5.0). New 20 G needles of brand a (referent) required 1.05 N to penetrate the standard material. One pass through a septum at the lowest recorded VVPF required an additional 0.09 N, an increase of 9% from baseline P < 0.0001, while 2 passes, both at the lowest recorded VVPF, required additional 0.21 (19%) N of force (P <0.0001). Compared to brand a, brand b and c required an additional 0.12 (11%) and 0.10 (10%) N, respectively, both P <0.0001. Smaller needles required less force, with 22, 25, and 29 G needles requiring -0.06 (-6%), -0.23 (-22%), and -0.47 (-45%) N, respectively (all P <0.003). VVPF increased the peak force by 0.03 N for each additional 0.5 N (P=0.003) during the first septum penetration, but was not significant for a second penetration (P=0.337). Fifty-two needles were scanned with the InfiniteFocus SL microscope after one and two passages through a vial septum. Twenty-one of 52 needles had visual defects after 1 passage and 27 had visual defects after 2 passages, which was not different (P = 0.241). Only VVPF was significant for predicting visual defects (OR 4.6; P = 0.001). Passage once or twice through vial septa resulted in less than a 20% change in force required to penetrate standard material. The impact of other factors, including brand, needle size, and force used to penetrate the vial, all had a greater impact on force than passage through a single vial septum. The clinical significance of these peak force differences is unknown.

FusionVision: A Comprehensive Approach of 3D Object Reconstruction and Segmentation from RGB-D Cameras Using YOLO and Fast Segment Anything.

In the realm of computer vision, the integration of advanced techniques into the pre-processing of RGB-D camera inputs poses a significant challenge, given the inherent complexities arising from diverse environmental conditions and varying object appearances. Therefore, this paper introduces FusionVision, an exhaustive pipeline adapted for the robust 3D segmentation of objects in RGB-D imagery. Traditional computer vision systems face limitations in simultaneously capturing precise object boundaries and achieving high-precision object detection on depth maps, as they are mainly proposed for RGB cameras. To address this challenge, FusionVision adopts an integrated approach by merging state-of-the-art object detection techniques, with advanced instance segmentation methods. The integration of these components enables a holistic (unified analysis of information obtained from both color RGB and depth D channels) interpretation of RGB-D data, facilitating the extraction of comprehensive and accurate object information in order to improve post-processes such as object 6D pose estimation, Simultanious Localization and Mapping (SLAM) operations, accurate 3D dataset extraction, etc. The proposed FusionVision pipeline employs YOLO for identifying objects within the RGB image domain. Subsequently, FastSAM, an innovative semantic segmentation model, is applied to delineate object boundaries, yielding refined segmentation masks. The synergy between these components and their integration into 3D scene understanding ensures a cohesive fusion of object detection and segmentation, enhancing overall precision in 3D object segmentation.

Transfer learning achieves high recall for object classification in fluvial environments with limited data

Field surveys to collect data from fluvial ecosystems traditionally focus on specific phenomena related to geomorphology or hydrology. Low-cost unmanned aerial vehicles (UAVs) additionally empower the fast and massive collection of airborne photogrammetry, providing geospatially explicit information. This remote sensing data complements field surveys by offering contextual information on geomorphological conditions, including digital terrain models. AI-based image recognition can augment contextual information to extrapolate archetypal object classes through name labels, such as “gravel”, “sand”, “plant”, or “large wood”. However, obtaining sufficient ground truth data for these classifications, particularly in morphodynamic fluvial environments, is challenging and induces high costs. This study introduces a transfer learning approach to address the challenge of low data availability, enabling AI-based mapping of complex objects in fluvial landscapes. We leverage the learned general structure of a deep convolutional neural network (CNN) pre-trained on a broad range of images. The fixed latent features of the pre-trained CNN stem from GoogLeNet. A fixed feature extractor serves to classify objects with limited data amounts. Satisfactory performance is measured with a recall rate, expressing the ability of a model to find all occurrences of a class on an image. High spatial heterogeneity in the locations of measurements on the x-y plane improves model performance. With a minimum of 400 labeled instances, the model achieves a satisfactory 93.75-% recall for a “large wood” target class, providing evidence of the effectiveness of transfer learning in remote sensing for geomorphological studies. This ability to detect large woods in river environments is critical to restoration efforts as it helps create fish habitat, which is essential to supporting biodiversity.

Embedded Object Detection and Mapping in Soft Materials Using Optical Tactile Sensing

In this paper, we present a methodology that uses an optical tactile sensor for efficient tactile exploration of embedded objects within soft materials. The methodology consists of an exploration phase, where a probabilistic estimate of the location of the embedded objects is built using a Bayesian approach. The exploration phase is then followed by a mapping phase which exploits the probabilistic map to reconstruct the underlying topography of the workspace by sampling in more detail regions where there are expected to be embedded objects. To demonstrate the effectiveness of the method, we tested our approach on an experimental setup that consists of a series of quartz beads located underneath a polyethylene foam that prevents direct observation of the configuration and requires the use of tactile exploration to recover the location of the beads. We show the performance of our methodology using ten different configurations of the beads where the proposed approach is able to approximate the underlying configuration. We benchmark our results against a random sampling policy. Our empirical results show that our method outperforms the fully random policy in both the exploration and mapping phases. The exploration phase produces a better probabilistic map with fewer samples which enables an earlier transition to the mapping phase to reconstruct the underlying shape. On both the exploration and mapping phases, our proposed method presents a better consistency as compared to the random policy, with smaller standard deviation across the ten different bead configurations.

Simulation of Space Objects And Future Perspective of Mosul's Space Expansion Until 2027 Under The Ca-Markov Model

Urban growth simulation models have proven their great effectiveness over years, as through these models a geographic information base is built in which presented to planners and specialists in urban planning, and in light of this, informed and correct decisions are made. Therefore, this research focused on predicting changes in the types of land cover in the city of Mosul from 2007 to 2017 to reach a prediction for the year 2027 using the simulation models available in the IDRISI SELVA program, and through the compatibility between geographic information systems and remote sensing programs. The CA-MARKOV model was employed to predict the size of expected changes in the types of land cover and obtain an objective map signifying the spread spatial organisms. The results showed that the city of Mosul is expected to expand spatially in the category of built-up areas to an area of up to (18) km2, where the constructed areas are expected to occupy an area of up to (143.5) km2, and by (79%) of the city region. It is expected that the city will be overcrowded with urbanization and what remains of barren areas and agricultural areas, are very limited and not commensurate with the increase of the city’s population, as it is expected to reach a number of (2,119,363) people in in the year 2027. Consequently, the research suggested expanding outside the city borders for a distance of 7 km2 in all directions by referring to experts in this field in order for the city to be built on a planned approach that does not distort its shape and grow more green spaces.

Single-shot synthetic wavelength imaging: Sub-mm precision ToF sensing with conventional CMOS sensors

We present a novel single-shot interferometric ToF camera targeted for precise 3D measurements of dynamic objects. The camera concept is based on Synthetic Wavelength Interferometry, a technique that allows retrieval of depth maps of objects with optically rough surfaces at submillimeter depth precision. In contrast to conventional ToF cameras, our device uses only off-the-shelf CCD/CMOS detectors and works at their native chip resolution (as of today, theoretically up to 20 Mp and beyond). Moreover, we can obtain a full 3D model of the object in single-shot, meaning that no temporal sequence of exposures or temporal illumination modulation (such as amplitude or frequency modulation) is necessary, which makes our camera robust against object motion.In this paper, we introduce the novel camera concept and show the first measurements that demonstrate the capabilities of our system. We present 3D measurements of small (cm-sized) objects with > 2 Mp point cloud resolution (the native pixel resolution of our used detector) and up to sub-mm depth precision. We also report a “single-shot 3D video” acquisition and a first single-shot “Non-Line-of-Sight” measurement. Our technique has great potential for high-precision applications with dynamic object movement, e.g., in AR/VR, industrial inspection, medical imaging, and imaging through scattering media like fog or human tissue.