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The fisheye system belongs to the family of ultra-wide field of view lenses and has various applications in science, industry, surveillance and artistic fields. Such lenses can cover a field of view of 180 degrees or even larger in the shape of a hemisphere, and therefore can provide the possibility of imaging a large part of the surrounding space with just one shot. Due to the wide temperature changes in Iran, the optical performance of this system is significantly reduced under the influence of the change in the radius and thickness of the surfaces and the change in the refractive index of its glasses. Therefore, in order to achieve optical-thermal stability in the temperature range of Iran, it is necessary to athermalize the system so that temperature changes do not cause a noticeable decrease in the optical performance of the system. In this work, a type of fisheye optical system is redesigned in the visible light spectrum bandwidth and then it is athermalized in the temperature range of Iran from -46 to 70 degrees Celsius. [ABSTRACT FROM AUTHOR]

The leaf area index (LAI) is an essential indicator for assessing vegetation growth and understanding the dynamics of forest ecosystems and is defined as the ratio of the total leaf surface area in the plant canopy to the corresponding surface area below it. LAI has applications for obtaining information on plant health, carbon cycling, and forest ecosystems. Due to their price and portability, mobile devices are becoming an alternative to measuring LAI. In this research, a new method for estimating LAI using a smart device with a fisheye lens (SFL) is proposed. The traditional Otsu method was enhanced to improve the accuracy and efficiency of foreground segmentation. The experimental samples were located in Gansu Ziwuling National Forest Park in Qingyang. In the accuracy parameter improvement experiment, the variance of the average LAI value obtained by using both zenith angle segmentation and azimuth angle segmentation methods was reduced by 50%. The results show that the segmentation of the front and back scenes of the new Otsu method is more accurate, and the obtained LAI values are more reliable. In the efficiency parameter improvement experiment, the time spent is reduced by 17.85% when the enhanced Otsu method is used to ensure that the data anomaly rate does not exceed 10%, which improves the integration of the algorithm into mobile devices and the efficiency of obtaining LAI. This study provides a fast and effective method for the near-ground measurement of forest vegetation productivity and provides help for the calculation of forest carbon sequestration efficiency, oxygen release rate, and forest water and soil conservation ability. [ABSTRACT FROM AUTHOR]

This study shows the results of the analysis of the photogrammetric use of 360-degree cameras in complex heritage-related scenes. The goal is to take advantage of the large field of view provided by these sensors and reduce the number of images used to cover the entire scene compared to those needed using conventional cameras. We also try to minimize problems derived from camera geometry and lens characteristics. In this regard, we used a multi-sensor camera composed of six fisheye lenses, applying photogrammetric procedures to several funerary structures. The methodology includes the analysis of several types of spherical images obtained using different stitching techniques and the comparison of the results of image orientation processes considering these images and the original fisheye images. Subsequently, we analyze the possible use of the fisheye images to model complex scenes by reducing the use of ground control points, thus minimizing the need to apply surveying techniques to determine their coordinates. In this regard, we applied distance constraints based on a previous extrinsic calibration of the camera, obtaining results similar to those obtained using a traditional schema based on points. The results have allowed us to determine the advantages and disadvantages of each type of image and configuration, providing several recommendations regarding their use in complex scenes. [ABSTRACT FROM AUTHOR]

A novel wider field of view of concentrators, which is composed of an optical fisheye lens with wider field of view and a traditional compound parabolic concentrator (CPC), is proposed in this paper. In this novel concentrator, exits of rays of meniscus fisheye lens and entrances of rays of CPC is fitted tightly on the basis of principles of ray trace, so that the proposed concentrator can be used to concentrate higher optical power than traditional CPC. In this paper, based on the geometry construction model of the new wide-field concentrator is established, the optics simulation software of TracePro is employed to model and design the structure of the concentrator, and analyses of performances for the concentrator is also carried out. The results show that this new wide-field concentrator can significantly increase the light energy received by the concentrator compared with a conventional concentrator without a wide-field fisheye lens, and can significantly improve the performance of LED wireless optical communication systems if used in the receiving optical antenna of LED wireless optical communication systems. [ABSTRACT FROM AUTHOR]

To achieve a lightweight design and wide field of view for the automatic alignment system in wireless optical communication, in the receiving antenna—a fisheye lens is incorporated as the receiving optical system. This feature enables the detection and tracking of lasers. The system utilizes a micro motor as the control servo system and a four-quadrant detector as the detection unit. Sequential and non-sequential ray tracing techniques were used to simulate the analysis of the fish-eye lens. Point array diagrams, ray trace diagrams, and encircled energy analysis were utilized to evaluate the spot's quality. The simulation results demonstrate that the fish-eye lens has a field of view of 120°, and the spot with 80% energy has a diameter smaller than 30 μm. The experimental results indicate that the fish-eye lens effectively captures the light beam within the range of ±30°. The simulated and experimental results for the sum and difference frequency amplitudes show good agreement. The outdoor experiments have demonstrated a tracking error of 22.757 μrad in this system. After alignment, the average output optical power of the detector is 3.23 μW, and the detected waveform amplitude is 12.48 mV. These findings demonstrate the system's potential for automatic alignment in wireless optical communication. Additionally, the system is relatively simple and practical. [ABSTRACT FROM AUTHOR]

This comprehensive study delves into the intricacies of trinocular camera configurations for feature-based Visual Odometry (VO) in aerial robotics, emphasizing a comparative analysis of the proposed trinocular Stereo Feature Matching (SFM) methodologies in terms of computational efficiency and accuracy against the established binocular SFM by comparing their VO results. It focuses on two canonical trinocular camera setups: in-line and 45-degree, each incorporating a rectilinear or 180-degree field-of-view fisheye lens for the third camera. The in-line configuration positions an additional camera at the center of a binocular setup, facilitating a systematic coarse-to-fine search in stereo feature matching. The 45-degree setup introduces a triangular camera arrangement, altering the epipolar line’s gradient from 0 to 45 degrees to enhance the reliability of stereo feature matching during a coarse-to-fine search similar to that of the in-line configuration. The proposed VO methodology is rigorously tested within a simulated quadrotor flight environment, created explicitly for this study using the Unity game engine to replicate realistic outdoor navigation scenarios. The simulation features a dynamically accurate quadrotor model to generate synchronized trinocular image sets, providing a robust platform for evaluating the VO approaches. The findings highlight that the 45-degree setup with a rectilinear lens for the third camera improves the binocular SFM for VO and decreases the computational cost to less than half, albeit at the expense of obtaining and storing an additional image at each instance.

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To achieve a lightweight design and wide field of view for the automatic alignment system in wireless optical communication, in the receiving antenna—a fisheye lens is incorporated as the receiving optical system. This feature enables the detection and tracking of lasers. The system utilizes a micro motor as the control servo system and a four-quadrant detector as the detection unit. Sequential and non-sequential ray tracing techniques were used to simulate the analysis of the fish-eye lens. Point array diagrams, ray trace diagrams, and encircled energy analysis were utilized to evaluate the spot’s quality. The simulation results demonstrate that the fish-eye lens has a field of view of 120°, and the spot with 80% energy has a diameter smaller than 30 μm. The experimental results indicate that the fish-eye lens effectively captures the light beam within the range of ±30°. The simulated and experimental results for the sum and difference frequency amplitudes show good agreement. The outdoor experiments have demonstrated a tracking error of 22.757 μrad in this system. After alignment, the average output optical power of the detector is 3.23 μW, and the detected waveform amplitude is 12.48 mV. These findings demonstrate the system’s potential for automatic alignment in wireless optical communication. Additionally, the system is relatively simple and practical.

This study shows the results of the analysis of the photogrammetric use of 360-degree cameras in complex heritage-related scenes. The goal is to take advantage of the large field of view provided by these sensors and reduce the number of images used to cover the entire scene compared to those needed using conventional cameras. We also try to minimize problems derived from camera geometry and lens characteristics. In this regard, we used a multi-sensor camera composed of six fisheye lenses, applying photogrammetric procedures to several funerary structures. The methodology includes the analysis of several types of spherical images obtained using different stitching techniques and the comparison of the results of image orientation processes considering these images and the original fisheye images. Subsequently, we analyze the possible use of the fisheye images to model complex scenes by reducing the use of ground control points, thus minimizing the need to apply surveying techniques to determine their coordinates. In this regard, we applied distance constraints based on a previous extrinsic calibration of the camera, obtaining results similar to those obtained using a traditional schema based on points. The results have allowed us to determine the advantages and disadvantages of each type of image and configuration, providing several recommendations regarding their use in complex scenes.

This study presents a visual-only odometry technique of a low-profile pallet robot using image feature tracking in ground plane images generated from a fisheye camera. The fisheye camera is commonly used in many robot vision applications because it provides a larger field of view (FoV) around a robot. However, because of the large radial distortion, the fisheye image is generally converted to a pinhole image for visual feature tracking or matching. Although the radial distortion can be eliminated via image undistortion with the lens calibration parameters, it causes several side effects, such as degraded image resolution and a significant reduction in the FoV. In this paper, instead of using the pinhole model, we propose to generate a ground plane image (GPI) from the fisheye image. GPI is a virtual top-view image that only contains the ground plane at the front of the robot. First, the original fisheye image is projected to several virtual pinhole images to generate a cubemap. Second, the front and bottom faces of the cubemap are projected to a GPI. Third, the GPI is homographically transformed again to further reduce image distortion. As a result, an accurate ortho-rectified ground plane image is obtained from the virtual top-view camera. For visual odometry using the ortho-rectified GPI, a number of 2D motion vectors are obtained using feature extraction and tracking between the previous and current frames in the GPI. By calculating a scaled motion vector, which is the measurement of the virtual wheel encoder of the mobile robot, we estimate the velocity and steering angle of the virtual wheel using the motion vector. Finally, we estimate the pose of the mobile robot by applying a kinematic model to the mobile robot. [ABSTRACT FROM AUTHOR]

In this study, an IoT-based fire detection system was developed to detect and prevent damage from forest fires at an early stage. In Korea, forest fires spread quickly due to the dry climate and winds in spring and autumn, so quick detection and prevention is necessary. To quickly detect and prevent forest fires that occur periodically, a real-time fire detection system was developed by combining a Raspberry Pi and a fisheye camera. A lens with a 220° angle of view was installed, and an image analysis algorithm was implemented using the OpenCV library. The location of the fire was estimated by calculating the polar coordinates of the omnidirectional images. Using the Wi-Fi communication function of the Raspberry Pi, the acquired continuous images were transmitted to the Firebase database, and the images were analyzed to identify the movement path of the forest fire. The developed system was applied to a mountainous area near the Samcheok Campus of Kangwon National University. As a result of the experiment, when the location of points about 25.9 m (average) away from the observation point was predicted, the positional error was analyzed to be about 1.1 m. If the system is improved in the future, it is expected that it will be able to contribute to the early prevention of forest fires with fast and accurate responses. [ABSTRACT FROM AUTHOR]

This article considers the synthesis of feedback controllers for a class in which strong robust stability is required against sensing errors. The motivation dealing with this class arises from the stabilization problem of a cart-driven inverted pendulum by visual feedback control using a fisheye lens. While fisheye lenses guarantee a wide-angle of view, a large image distortion at off-center area is inevitable. Therefore this study first derives a geometric measurement model of a pendulum angle using a general fisheye lens model. A new design method for robust controllers for our problem is then proposed. Finally, a robust feedback controller that allows lens distortion is designed. The effectiveness of the controller based on the proposed model and the proposed design method is verified through numerical simulations and experiments. [ABSTRACT FROM AUTHOR]

This study presents a visual-only odometry technique of a low-profile pallet robot using image feature tracking in ground plane images generated from a fisheye camera. The fisheye camera is commonly used in many robot vision applications because it provides a larger field of view (FoV) around a robot. However, because of the large radial distortion, the fisheye image is generally converted to a pinhole image for visual feature tracking or matching. Although the radial distortion can be eliminated via image undistortion with the lens calibration parameters, it causes several side effects, such as degraded image resolution and a significant reduction in the FoV. In this paper, instead of using the pinhole model, we propose to generate a ground plane image (GPI) from the fisheye image. GPI is a virtual top-view image that only contains the ground plane at the front of the robot. First, the original fisheye image is projected to several virtual pinhole images to generate a cubemap. Second, the front and bottom faces of the cubemap are projected to a GPI. Third, the GPI is homographically transformed again to further reduce image distortion. As a result, an accurate ortho-rectified ground plane image is obtained from the virtual top-view camera. For visual odometry using the ortho-rectified GPI, a number of 2D motion vectors are obtained using feature extraction and tracking between the previous and current frames in the GPI. By calculating a scaled motion vector, which is the measurement of the virtual wheel encoder of the mobile robot, we estimate the velocity and steering angle of the virtual wheel using the motion vector. Finally, we estimate the pose of the mobile robot by applying a kinematic model to the mobile robot.

In this study, an IoT-based fire detection system was developed to detect and prevent damage from forest fires at an early stage. In Korea, forest fires spread quickly due to the dry climate and winds in spring and autumn, so quick detection and prevention is necessary. To quickly detect and prevent forest fires that occur periodically, a real-time fire detection system was developed by combining a Raspberry Pi and a fisheye camera. A lens with a 220° angle of view was installed, and an image analysis algorithm was implemented using the OpenCV library. The location of the fire was estimated by calculating the polar coordinates of the omnidirectional images. Using the Wi-Fi communication function of the Raspberry Pi, the acquired continuous images were transmitted to the Firebase database, and the images were analyzed to identify the movement path of the forest fire. The developed system was applied to a mountainous area near the Samcheok Campus of Kangwon National University. As a result of the experiment, when the location of points about 25.9 m (average) away from the observation point was predicted, the positional error was analyzed to be about 1.1 m. If the system is improved in the future, it is expected that it will be able to contribute to the early prevention of forest fires with fast and accurate responses.

Fisheye lens cameras are widely used in such applications where a large field of view (FOV) is necessary. A large FOV can provide an enhanced understanding of the surrounding environment and can be an effective solution for detecting the objects in automotive applications. However, this comes with the cost of strong radial distortions and irregular size of objects depending on the location in an image. Therefore, we propose a new fisheye image warping method called Expandable Spherical Projection to expand the center and boundary regions in which smaller objects are mostly located. The proposed method produces undistorted objects especially in the image boundary and a less unwanted background in the bounding boxes. Additionally, we propose three multi-scale feature concatenation methods and provide the analysis of the influence from the three concatenation methods in a real-time object detector. Multiple fisheye image datasets are employed to demonstrate the effectiveness of the proposed projection and feature concatenation methods. From the experimental results, we find that the proposed Expandable Spherical projection and the LCat feature concatenation yield the best AP performance, which is up to 4.7% improvement compared to the original fisheye image datasets and the baseline model. [ABSTRACT FROM AUTHOR]

Background: Compared to benchtop ultrasound machines, mobile ultrasound machines require portable batteries when acquiring information regarding human tissues during outdoor activities.Objective: A novel fisheye lens type was designed to address the charging issue where it is difficult to constantly track the sun. This method does not require the use of a mechanical motor that constantly tracks the sun to charge the portable batteries.Methods: To obtain an optical solar power system, the numerical aperture (NA) and field angle must be increased. Therefore, we use the fisheye lens with the largest field angle.Results: The NA of the designed fisheye lens system reaches 0.75, allowing light collection of approximately ± 48∘. Additionally, the efficiency ratio of the central and surrounding areas also satisfies more than 80% at a field angle of 85∘ and more than 70% at field angles of 85∘ to 90∘, respectively.Conclusions: We designed a novel fisheye lens for solar-powered mobile ultrasound machines used outdoors. [ABSTRACT FROM AUTHOR]

The article is devoted to the issue of measuring the angular resolution characteristics and the modulation transmission function of panoramic video cameras, which determine the information content of the entire television system. A technique for assessing the potential capabilities of panoramic TV cameras in terms of object detection and recognition is considered. The found characteristics make it possible to calculate the permissible distance to the objects of interest if the linear dimensions of these objects are known.

Multibeam (MB) radiations of antenna arrays rely on effective beamforming networks (BFNs). A 2-D fisheye lens-based BFN (FL-BFN) was developed using a half 2-D lens realizable on metal parallel-plate sandwiched substrates to excite a planar antenna array. This FL-BFN implemented the beam and antenna excitation ports on its half-circular circumference and straight boundaries. An optimization scheme was developed to minimize the ray propagation distortion due to an incomplete half-lens propagation path for an offset beam, which results in an aperiodic array of antennas for MB radiations. Excitations for periodic arrays can also be implemented by considering an aperiodic output port establishment. The rule to determine the positions of antenna elements is also shown for easy design. This FL-BFN performance is demonstrated using its output amplitudes and phases to excite a Vivaldi antenna array for MB radiation. Numerical simulations and measurements over a prototype were performed to validate its feasibility with distinguished agreements. [ABSTRACT FROM AUTHOR]

Images acquired by a fisheye lens camera contain geometric distortion that results in deformation of the object's shape. To correct the lens distortion, existing methods use prior information, such as calibration patterns or lens design specifications. However, the use of a calibration pattern works only when an input scene is a 2-D plane at a prespecified position. On the other hand, the lens design specifications can be understood only by optical experts. To solve these problems, we present a novel image-based algorithm that corrects the geometric distortion. The proposed algorithm consists of three stages: i) feature detection, ii) distortion parameter estimation, and iii) selection of the optimally corrected image out of multiple corrected candidates. The proposed method can automatically select the optimal amount of correction for a fisheye lens distortion by analyzing characteristics of the distorted image using neither prespecified lens design parameters nor calibration patterns. Furthermore, our method performs not only on-line correction by using facial landmark points, but also off-line correction described in subsection III-C. As a result, the proposed method can be applied to a virtual reality (VR) or augmented reality (AR) camera with two fisheye lenses in a field-of-view (FOV) of 195°, autonomous vehicle vision systems, wide-area visual surveillance systems, and unmanned aerial vehicle (UAV) cameras.

Fisheye lens cameras are widely used in such applications where a large field of view (FOV) is necessary. A large FOV can provide an enhanced understanding of the surrounding environment and can be an effective solution for detecting the objects in automotive applications. However, this comes with the cost of strong radial distortions and irregular size of objects depending on the location in an image. Therefore, we propose a new fisheye image warping method called Expandable Spherical Projection to expand the center and boundary regions in which smaller objects are mostly located. The proposed method produces undistorted objects especially in the image boundary and a less unwanted background in the bounding boxes. Additionally, we propose three multi-scale feature concatenation methods and provide the analysis of the influence from the three concatenation methods in a real-time object detector. Multiple fisheye image datasets are employed to demonstrate the effectiveness of the proposed projection and feature concatenation methods. From the experimental results, we find that the proposed Expandable Spherical projection and the LCat feature concatenation yield the best AP performance, which is up to 4.7% improvement compared to the original fisheye image datasets and the baseline model.

A design method of aspheric fisheye lens has been proposed in this paper, based on the requirements of automobile surround view system. The study has designed a kind of ultra-wide-angle fisheye lens, which only consists of a spherical glass lens and three aspherical plastic lenses. The maximum diameter of imaging aperture is 15. 3 mm; the working distance behind is 2.158 mm; the total length of system is 11.44 mm; the focal length is 0.97 mm; the viewing angle is 210°, and the modulation transfer function (MTF) curve is 0.35 at 60 lp/mm. Furthermore, a kind of a distortion correction algorithm for fisheye lens has been created, which calculates the position of the ideal image point with the actual image point and the obtained distortion curve and distortion model. The algorithm can correct the distorted image taken by a fisheye lens to an image without distortion, which is suitable for the human eye. The algorithm, which is simple and effective, has been applied to the automobile surround view system. It has been verified to be accurate and reasonable, after the comparison is made between the real image taken by a fisheye lens and the corrected image. [ABSTRACT FROM AUTHOR]

The frequency of pedestrian traffic accidents continues to increase in Japan. Thus, a driver assistance system is expected to reduce the number of accidents. However, it is difficult for the current environmental recognition sensors to detect crossing pedestrians when turning at intersections, owing to the field of view and the cost. We propose a pedestrian detection system that utilizes surround-view fisheye cameras with a wide field of view. The system can be realized at low cost if the fisheye cameras are already equipped. It is necessary to detect the positioning of pedestrians accurately because more precise prediction of future collision points is required at intersections. Stereo vision is suitable for this purpose. However, there are some concerns regarding realizing stereo vision using fisheye cameras due to the distortion of the lens, asynchronous capturing, and fluctuating camera postures. As a countermeasure, we propose a novel method combining various machine-learning techniques. The D-Brief with histogram of oriented gradients and normalized cross-correlation are combined by a support-vector machine for stereo matching. A random forest was adopted to discriminate the pedestrians from noise in the 3D reconstructed point cloud. We evaluated this for images of crossing pedestrians at actual intersections. A tracking rate of 96.0% was achieved as the evaluation result. It was verified that this algorithm can accurately detect a pedestrian with an average position error of 0.17 m. [ABSTRACT FROM AUTHOR]

Methods of monitoring tunnel interior walls have mainly focused on laser scanners or line scan cameras. In this study, we propose a method of acquiring images of tunnel interior walls using a fisheye lens camera. First, we produce rectangular images that include the tunnel walls and floors by applying a cylindrical projection transformation to the circular fisheye lens images. Distortions are corrected to produce more realistic images, which are then connected to produce a tunnel mosaic image. The advantage of this method is that it can save working time and relatively reduce costs. The tunnel mosaic image produced by our method can be used for tunnel surface inspection to detect problems such as large cracks, efflorescence caused by water leakage, and exfoliation. [ABSTRACT FROM AUTHOR]

• A low-cost fisheye lens and a smartphone quantify the shading correction factor. • The method does not require 3D building design or angle measurements. • The model correctly predicts the real Sun's position in the photos. • The model correctly predicts the expected window shading. • Standard tabulated values do not take into account overlapping shading. Quasi-steady-state methods to calculate monthly heating and cooling energy needs require the quantification of solar heat gains through windows. The presence of external obstacles, such as natural topography, other buildings, overhangs, or side fins, may significantly decrease solar gains. Simplified methods to evaluate shading on windows throughout the year use the shading correction factor concept, i.e., the ratio between the surface solar irradiation in the presence of external obstacles and in their absence. This paper presents a photographic method using a low-cost fisheye lens attached to a smartphone to quantify the shading correction factor. It is based on image processing, solar geometry, and climate databases and does not require 3D building design or angle measurement of external obstacles. Both beam and diffuse correction factors are calculated monthly. The model correctly predicts the real Sun's position in the photos and the expected monthly shading of a South window with an overhang. For the diffuse correction factor, errors up to 11% are obtained when compared to the analytical solution of a window with a large overhang. Standard tabulated values for windows with multiple obstructions are conservative when compared to those of the photographic method. The tabulated approach considers the effect of various obstacles shading even when overlapping occurs, which possibly explains the difference between methods. [ABSTRACT FROM AUTHOR]

• A single-source full-duplex modulating retroreflector UWOC system is proposed. • Modulating retroreflection is achieved by MEMS grating modulator and fisheye lens. • Large field of view over 130° is experimentally verified. • Ensure BER under FEC limit at low received optical power of −47 dBm using SiPM. In this paper, a single source full-duplex modulating retroreflector based underwater wireless optical communication (UWOC) system is proposed and experimentally demonstrated. A green laser is used and directly modulated for the downlink data transmission, and a reflective MEMS grating modulator is employed in the uplink to reflect and modulate the transmitting light. A large field-of-view (FOV) fisheye lens is mounted before the MEMS grating modulator to extend the field of view of the transceiver. The received signal in uplink, of which light beam travels through the underwater channel twice, is detected by a highly sensitive silicon photomultiplier (SiPM). The BER performance of the system is comprehensively investigated at different received optical powers and different incident angles. Experimental results show that the system can achieve 200-kbps uplink data rate and at 1.6-Gbps downlink data rate simultaneously at a wide field-of-view at 130°, offering a promising system design for practical applications such as data collection and controlling of small and lightweight underwater devices. To the best of our knowledge, it is the first time that Modulating retroreflector (MRR) based full-duplex UWOC system with only one light source has been experimentally demonstrated and studied. The achievable transmission distances of the proposed system at different water types are estimated, which are about 49 m and 15 m, in pure sea water and clear ocean water respectively. [ABSTRACT FROM AUTHOR]

Subject of Study. The key feature of spherical panoramas is the maximum possible angle of view (360 × 180 degrees). Omnidirectional optical-electronic systems are able to produce images that show most of this space, but these images are different from the canonical spherical panoramas. This paper proposes a method of converting the circular images obtained by omnidirectional optical systems, to canonical spherical panoramic images with the use ofcalibration procedure of omnidirectional optical-electronic system. Method. The process of spherical panoramas creation consists of three steps.The first step includesthe forming of virtual surface in the object space corresponding to a field of view of the spherical panorama. The surface is defined by the three-dimensional array of pixels.At the second step the coordinates of images of these points in the plane of the detectorare specified. At the third step pixel-by-pixel forming of the output imageisperformed from the original omnidirectional image with the use of coordinates obtained at the second step. Main Results. We have considered the geometric projectionmodel of spherical panoramas. The algorithm has been proposed calculating the three-dimensional array of pixels, characterizing the field of view of a spherical panorama and convenient for practical usage. The developed method is designed to work with omnidirectional optical-electronic systems both with catadioptric optical systems and with fisheye lens. Experimental results confirming the validity of this method are presented. The reprojection mean-square error was equal to 0.794 px. Practical Relevance. The proposed method can be applied in technologies of creating of virtual tours or panoramas of streets where spherical panoramic images are the standard for storing visual information. The method may also find its application in various fields of robotics, orientation and navigation of space vehicles and UAVs.

We propose an interpolation method considering strong barrel distortion of a fisheye lens using nearest pixels on a corrected image. The correction of barrel distortion comprises coordinate transformation and interpolation, and this paper focuses on interpolation. The proposed interpolation method uses nearest coordinates on a corrected image rather than on a distorted image, unlike existing techniques. The increased computational complexity of the proposed interpolation method is alleviated by using look-up table (LUT)-based optimization. Experimental results show that both subjective and objective image qualities are improved with marginal execution time. [ABSTRACT FROM AUTHOR]

This paper proposes a noble avoidance control algorithm based on omni-directional visual simultaneous localization and mapping (OVSLAM) with a fisheye lens camera. In addition, a robot avoids colliding with an obstacle regardless of the obstacle’s state by analyzing the information of the object obtained from an OVSLAM approach. OVSLAM has many advantages for object detection and mapping because it can measure all information around a robot simultaneously. We therefore proposed an improved avoidance and formation control to configure a multi-robot system optimized for OVSLAM. This system creates a global map based on vector information and position information of objects obtained from a local map, and determines the avoidance method according to the type of object, which is classified by analyzing the odometry and vector and position information. We carried out a formation control experiment in an environment with static obstacles and a dynamic robot, and a formation control experiment in an environment with dynamic obstacles and a robot. The reliability of the proposed formation algorithm was verified through a comparison of maps based on the proposed algorithm and real maps while maintaining the formation by applying a real robot. [ABSTRACT FROM AUTHOR]

Visual perception is regularly used by humans and robots for navigation. By either implicitly or explicitly mapping the environment, ego-motion can be determined and a path of actions can be planned. The process of mapping and navigation are delicately intertwined; therefore, improving one can often lead to an improvement of the other. Both processes are sensitive to the interior orientation parameters of the camera system and mathematically modelling these systematic errors can often improve the precision and accuracy of the overall solution. This paper presents an automatic camera calibration method suitable for any lens, without having prior knowledge about the sensor. Statistical inference is performed to map the environment and localize the camera simultaneously. K-nearest neighbour regression is used to model the geometric distortions of the images. A normal-angle lens Nikon camera and wide-angle lens GoPro camera were calibrated using the proposed method, as well as the conventional bundle adjustment with self-calibration method (for comparison). Results showed that the mapping error was reduced from an average of 14.9 mm to 1.2 mm (i.e. a 92% improvement) and 66.6 mm to 1.5 mm (i.e. a 98% improvement) using the proposed method for the Nikon and GoPro cameras, respectively. In contrast, the conventional approach achieved an average 3D error of 0.9 mm (i.e. 94% improvement) and 6 mm (i.e. 91% improvement) for the Nikon and GoPro cameras, respectively. Thus, the proposed method performs more consistently, irrespective of the lens/sensor used: it yields results that are comparable to the conventional approach for normal-angle lens cameras, and it has the additional benefit of improving calibration results for wide-angle lens cameras. [ABSTRACT FROM AUTHOR]

Due to the limitedmodulation bandwidth of commercial light emitting diodes (LEDs), imaging optical multiple-input multiple-output (MIMO) technology is applied in visible light communication (VLC) system to achieve high data rate. Since a receiver with a wide angle/field-of-view is preferred in the imaging optical MIMO VLC system, the fisheye lens can be utilized to concentrate the lights from the LEDs. To eliminate the inter-user interference and satisfy their target bit error rate (BER) requirements with the minimum number of LEDs, an interference-free LED allocation scheme is investigated in this paper, which is formulated as a combinatorial problem. The cost criterion of the combinatorial problem is defined as the number of the LEDs used to serve all users, and its discrete alternatives (i.e., feasible solutions) are the disjoint sets consisting of the LEDs that can be cooperatively utilized to satisfy the BER requirements for all users. For each LED in the disjoint set, its neighboring LEDs projected onto the same pixel are forbidden to serve different users. Moreover, due to the NP-hardness of the formulated problem, a location-based greedy algorithm is proposed, where the LEDs are allocated to the users sequentially based on their distances to the center of the LED array. Simulation results verify the effectiveness of our proposed algorithm and show that there exists no interference among all users while the target BER requirements for all users are satisfied with the proposed algorithm. [ABSTRACT FROM AUTHOR]