Omnidirectional Camera Research Articles

Beyond videoconferencing: enhancing remote home assessments with 3D modeling technology

Purpose: Occupational therapists in the Veterans Health Administration have transitioned from in-person to videoconferencing for home assessments, benefiting Veterans living in remote and rural areas. However, videoconferencing has limitations, including restricted field of view and poor video quality, affecting hazard identification accuracy. This study aims to introduce and evaluate a three-dimensional (3D) model as an alternative technology for remote home assessments. Materials and methods: We created 3D models using a 360-degree camera and mobile app. Five occupational therapists individually completed virtual training and practice sessions to familiarize themselves with using the 3D model. Each participant then conducted a remote home assessment using the 3D model and completed questionnaires, System Usability Scale (SUS), and semi-structured interviews. Results: Participants spent an average of 10 min training and practicing with the 3D model, and most reported either maintaining or gaining confidence in using it compared to before. All participants successfully completed the assessments, which took an average of 17 min. They rated the 3D model as easy to use, with an average SUS score of 78.5. Participants preferred the 3D model over videoconferencing, noting that it effectively addressed current challenges, and expressed their willingness to integrate it into clinical practice. Conclusion: This study demonstrates that 3D models offer a promising option for remote home assessments. With minimal training, occupational therapists could conduct more effective assessments. It is recommended to use 3D models for an initial understanding of the home environment before videoconferencing-based assessments to enhance the remote assessment experience for occupational therapists and clients.

Application of 360 Camera Technology and Excavator Operator Workload at a Nickel Ore Mine and Its Implication for Work Accident Rates Using the Nasa-TLX Method

Indonesia, as one of the largest nickel producers in the world, has around 90% of nickel reserves spread across various regions, such as Central Sulawesi, South Sulawesi, Southeast Sulawesi, and North Maluku. Even though demand for nickel continues to increase, a severe problem that needs attention is the rate of work accidents in mining fields. Most heavy equipment accidents that occur are caused by operator negligence while operating. This negligence can occur when operators are in a hurry, make mistakes while using heavy equipment, or do not have proper work time management. This research aims to analyze the impact of 360-degree camera technology on excavator operators in nickel ore mines on work accident rates and operator workload. The case study was carried out at PT Rifky and Raisha Anursyah using the NASA-TLX method to measure workload. In contrast, the number of accidents that occurred to each operator within one month was used to measure work accidents. The 360 camera technology provides a comprehensive view of the work environment, allowing operators to monitor the surrounding area better and reduce blind spots. The research results show that applying this technology can reduce the risk of work accidents and increase the work efficiency of excavator operators. With better monitoring, operators can identify potential hazards earlier and reduce the risk of accidents. Workload evaluation using NASA-TLX shows a decrease in operator workload after implementing 360 camera technology. This research provides strategic recommendations for workload management and implementing safety technology in the mining industry.

Accuracy of fish-eye camera device for aircraft positioning based on laboratory experiment combining computer graphic and 3D Projection

For the management of airborne mobility devices such as airplanes and UAVs, such as noise assessment, it is important to measure the three-dimensional position of the aircraft, and various technologies have been researched and developed. We have developed an Aircraft Positioning Camera (APC) based on an IoT device equipped with a fisheye camera that can mechanically measure aircraft position at a local area with low cost and with high mobility. The performance of this APC is still uncertain as to the limits of the flight altitude and speed of the aircraft that can be measured. Therefore, a detailed study of its performance is needed. Since, it is difficult to standardize the conditions such as weather and ground surface conditions, it is effective to conduct these studies in a laboratory where environmental changes can be controlled. The performance of this APC was examined at an experimental facility where images captured by a 360-degree camera or computer graphics can be projected in three dimensions onto a hemispherical dome.

Optimizing Additive Manufacturable Structures with Computer Vision to Enhance Material Efficiency and Structural Stability

This study introduces an innovative technique that merges computer vision with topology optimization to advance additive manufacturing. Employing advanced photogrammetry software, we obtain high-resolution images of the design domain, which are then used to develop accurate 3D models through meticulous scanning procedures. These models are transformed into an STL file format and remeshed using an adaptive algorithm within COMSOL 5.3 Multiphysics, facilitated by a custom MATLAB 2023 application. This integration achieves the optimal mesh resolution and precision in analytical assessments. We applied this technique to the design of a concrete pillar for 3D printing, targeting a 75% reduction in volume to improve the material efficiency and structural stability—critical factors for extraterrestrial applications. The design, captured with a 360-degree camera array, guided the MATLAB-based topology optimization process. By combining MATLAB’s optimization algorithms with COMSOL’s meshing and finite element analysis tools, we investigated various material-efficient configurations. The findings reveal a substantial volume reduction, especially in the central region of the design, effectively optimizing material utilization while preserving structural integrity. The optimization algorithm exhibited a swift and stable convergence, reaching near-optimal solutions within approximately 20 iterations.

On the use of a consumer-grade 360-degree camera as a radiometer for scientific applications

Improved miniaturization capabilities for complex fisheye camera systems have recently led to the introduction of many compact 360-degree cameras on the consumer technology market. Designed primarily for recreational photography, several manufacturers have decided to allow users access to raw imagery for further editing flexibility, thereby offering data at a sensor level that can be directly exploited for absolute-light quantification. In this study, we demonstrate methodologies to carefully calibrate a consumer-grade 360-degree camera for radiometry use. The methods include linearity analysis, geometric calibration, assessment of the illumination fall-off across the image plane, spectral-response determination, absolute spectral-radiance calibration, immersion factor determination, and dark-frame analysis. Accuracy of the calibration was validated by a real-world experiment comparing sky radiance measurements with a colocalized compact optical profiling system (C-OPS, Biospherical Instruments Inc.), which gave mean unbiased percentage differences of less than 21.1%. Using the photon-transfer technique, we calculated that this camera consisting of two fisheyes with a 182° field of view in air (152° in water) has a limit of detection of at least 4.6×10−7W⋅sr−1⋅m−2⋅nm−1 in its three spectral channels. This technology, with properly stored calibration data, may benefit researchers from multiple scientific areas interested in radiometric geometric light-field study. While some of these radiometric calibration methods are complex or costly, this work opens up possibilities for easy-to-use, inexpensive, and accessible radiance cameras.

Reflex-based open-vocabulary navigation without prior knowledge using omnidirectional camera and multiple vision-language models

Various robot navigation methods have been developed, but they are mainly based on Simultaneous Localization and Mapping (SLAM), reinforcement learning, etc., which require prior map construction or learning. In this study, we consider the simplest method that does not require any map construction or learning, and execute open-vocabulary navigation of robots without any prior knowledge to do this. We applied an omnidirectional camera and pre-trained vision-language models to the robot. The omnidirectional camera provides a uniform view of the surroundings, thus eliminating the need for complicated exploratory behaviors including trajectory generation. By applying multiple pre-trained vision-language models to this omnidirectional image and incorporating reflective behaviors, we show that navigation becomes simple and does not require any prior setup. Interesting properties and limitations of our method are discussed based on experiments with the mobile robot Fetch.

Catadioptric omnidirectional thermal odometry in dynamic environment

This paper presents a catadioptric omnidirectional thermal odometry (COTO) system that estimates the six degrees of freedom (DoF) pose of a camera using only omnidirectional thermal images in visually degraded, fast-motion, and dynamic environments. First, we design and fabricate a central hyperbolic catadioptric omnidirectional thermal camera that captures surrounding thermal images with 360° horizontal field of view (FoV), and improve the omnidirectional camera model and calibration method to obtain high-precision camera intrinsic parameter. Second, we propose the epipolar curve constraint combining with omnidirectional thermal object detection to significantly reduce the interference of moving objects on pose estimation. Third, the implemented COTO pipeline consists of photometric calibration, dynamic region removal, tracking and mapping to overcome the drawbacks of photometric inconsistency and large distortion in omnidirectional thermal images. Experiments have been conducted on a total of 17 sequences of Lab, Outdoor and Driving, amounting to more than 60,000 omnidirectional thermal images of real environments. The experimental results indicate that the proposed COTO system has excellent localization accuracy and unparalleled robustness over the current state-of-the-art methods. The average localization accuracy measured by the absolute trajectory error (ATE) is less than 15 cm from the ground truth in both Lab and Outdoor sequences. In addition, COTO was the only system with complete and successful tracking in all sequences. The system can be used as an innovative localization solution, particularly in challenging environments with changes in ambient light, rapid vehicle motion, and moving object interference, which can be a difficult problem for visual odometry to solve.

Designing for Networked Learning in 360VR - A scenographic turn in online learning environments?

Despite the growing popularity of Virtual Reality (VR) in Higher Education (HE), there is a lack of studies dealing with networked and collaborative activities in VR (Radianti et al., 2020). Historically, VR has been promoted as an educational technology that can give access to exotic places or dangerous situations through computer-generated virtual worlds. Another area of application of VR has been therapeutical sessions exposing individuals to unknown situations. Concepts like interactivity, immersion and presence has been shaping the discourse of educational VR (Markowitz & Bailenson, 2019), but that is not necessarily supporting a networked or collaborative learning approach. Recently, 360-degree video cameras has made it possible to record situated practices, which can then be used as the canvas in the virtual world (McIlvenny & Davidsen, 2017). Pirker et al. (2021) argued that 360VR could potentially be a game-changer for distant education, but it is also clear that 360VR pose a new medium for supporting Networked Learning. Basically, 360VR presents a transition from logocentric platforms (e.g. Moodle) emphasising the exchange of text between peers towards platforms that build upon ideas of immersion, inhabitation and multimodality. The aim of the workshop is to discuss how principles of Networked Learning can inform the design of 360VR activities in HE. CAVA360VR is a prototype Unity-based Windows application supporting 20 simultaneous participants to collaboratively analyse, visualise and annotate 360° video in VR. CAVA360VR is developed by the BigSoftVideo team (www.bigvideo.aau.dk) in Aalborg University (McIlvenny, 2020). In CAVA360VR, remote participants can share, view and interact with a 360° video together, draw on the 360° video, use a ‘mirror-cam’ to see what is behind you, use a laser pointer to guide others’ attention, import a 2D image, view a transcript, and view a synced 2D video with the 360° video. Further, participants can talk to each other, and the audio is spatialized in the VR environment. In CAVA360VR, each participant is represented with an avatar that follows the orientation of the Head Mounted Display (HMD) of the individual participant and the controllers are showed as pair of avatar hands. The potential of CAVA360VR is also particularly interesting in the context of Networked Learning as it offers a new platform for designing for learning. CAVA360VR is not only available in VR, but can also run as a standard desktop application, which allows a larger, mixed group to participate in the analysis of the recorded data. Not all of the features available in VR are available in non-VR mode. For two years, CAVA360VR has been used in many video data sessions (Jordan & Henderson, 1995; McIlvenny, 2020) with participants – for example, from Ghana, Finland and Denmark – analysing 360° video data together. The potential of CAVA360VR is also particularly interesting in the context of Networked Learning as it offers a new platform for designing for learning. This includes addressing how to collect 360 video data, how to pedagogically design activities, and how to support students negotiating of meaning in 360VR, etc.

Trinocular 360-degree stereo for accurate all-round 3D reconstruction considering uncertainty

This research proposes a method for accurate all-round 3D reconstruction of an indoor environment in one-shot using a system of trinocular 360-degree cameras. Binocular 360-degree stereo is unable to reconstruct in all directions due to lack of disparity along epipolar directions. Thus, a third camera along a perpendicular epipolar direction is introduced to cover for this, making the system trinocular. However, previous works with trinocular stereo did not adequately take into account the uncertainty of disparity estimation and geometric constraints around 3D reconstruction. Therefore, we propose a geometric optimization scheme considering disparity estimation uncertainty and show that this results in both higher accuracy and lesser outliers along epipolar directions, in both simulated and real environments.

Automatic detection of color markings and numbers on trees in point clouds from Personal Laser Scanning (PLS) and Terrestrial Laser Scanning (TLS)

In forestry, colored spray paint is used for different purposes, such as marking trees that are chosen for the next harvest or that will be promoted by future silvicultural activities, or for the demarcation of skid/cable roads. Numerous studies have demonstrated the application of Terrestrial Laser Scanners (TLS) and Personal Laser Scanners (PLS) for the acquisition of tree parameters (diameters, heights, and tree positions) in a forest inventory context. However, no studies have included classification based on spectral information by applying colored markings to trees. When a laser scanner is combined with a camera, the color information can be mapped onto the laser point cloud, allowing for additional analysis of spectral information. In this study, we have tested the analysis of joint information from imagery and 3D point clouds in two different settings: (i) PLS point cloud data from a GeoSLAM ZEB Horizon were complemented with spectral information from images collected with a NCTech iSTAR Pulsar 360-degree camera, (ii) TLS point cloud data from a RIEGL VZ-400i were combined with imagery from a Nikon D850 digital single lens reflex (DSLR) camera with 14 mm fisheye lens. The major objective was to automatically classify trees that were marked with colored sprays automatically identify the numbers sprayed on the trees. The marked trees could be classified correctly with a balanced accuracy of 77.26% for PLS and 98.01% for the data collected with the TLS system using a support vector machine (SVM) model. The numbers written on the trees were classified from the TLS data using a YOLOv8 model. The accuracy of the digit classification reached up to 97.30%. In conclusion, it is possible to automatically detect marked trees and to automatically recognize the numbers spayed on these trees from colored point cloud data. However, accuracy strongly depends on the selected combination of scanner and camera. The findings of future research on this subject might differ with the ongoing development of PLS systems and could be enhanced by creating a large dataset of handwritten numbers collected using laser scanning systems.

AV-FDTI: Audio-visual fusion for drone threat identification

In response to the evolving challenges posed by small unmanned aerial vehicles (UAVs), which have the potential to transport harmful payloads or cause significant damage, we present AV-FDTI, an innovative Audio-Visual Fusion system designed for Drone Threat Identification. AV-FDTI leverages the fusion of audio and omnidirectional camera feature inputs, providing a comprehensive solution to enhance the precision and resilience of drone classification and 3D localization. Specifically, AV-FDTI employs a CRNN network to capture vital temporal dynamics within the audio domain and utilizes a pretrained ResNet50 model for image feature extraction. Furthermore, we adopt a visual information entropy and cross-attention-based mechanism to enhance the fusion of visual and audio data. Notably, our system is trained based on automated Leica tracking annotations, offering accurate ground truth data with millimeter-level accuracy. Comprehensive comparative evaluations demonstrate the superiority of our solution over the existing systems. In our commitment to advancing this field, we will release this work as open-source code and wearable AV-FDTI design, contributing valuable resources to the research community.

Processing of Image captured by Omnidirectional Camera for Object Detection

Processing of Image captured by Omnidirectional Camera for Object Detection

Re-thinking housing inspection and regulation: using 360 technology as a new approach in environmental health practice training

Front-line professions such as environmental health require practitioners to demonstrate competence in practice-based skills typically gained only through on-the-job experience. However, practice opportunities have been more scarce, owing mainly to austerity but also to the impact of the COVID-19 pandemic, so necessitating novel approaches to teaching and learning. 360 technology has recently emerged as a possible solution, but its potential for use in an environmental health setting, such as housing inspection and regulation, is virtually unknown. This study involved the use of a 360-degree camera to record a simulated walkthrough and mock inspection of a two-storey house. These ‘photospheres’ were demonstrated to under- and postgraduate students, who were then surveyed online to explore their attitudes towards the use of this technology as a training method. Analysis of the questionnaire responses revealed four self-reported themes: experience of housing regulation and enforcement practice and training; experiences of 360 technology in housing inspection practice and enforcement; attitudes towards using 360 technology versus traditional photograph and filming methods for experiential learning, training and practice purposes; and attitudes towards the application of 360 technology for experiential learning and training purposes in housing inspection enforcement and regulation. The results indicated that students found this a helpful and flexible tool, particularly valuing its immersive nature, both for initial training and continuing professional development (CPD) in housing inspections and interventions. It has wider applicability to other frontline professional practices and requires further development to help shape new forms of training.

Analysis of the Photogrammetric Use of 360-Degree Cameras in Complex Heritage-Related Scenes: Case of the Necropolis of Qubbet el-Hawa (Aswan Egypt).

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.

Navigating parallel interactive narratives in virtual reality

ABSTRACT The application of Campbell’s hero’s journey in cinema commonly adopts a director-centric approach in which the director decides how the viewer will see the narrative. A parallel interactive narrative in virtual reality titled Table for Two adopts screen production enquiry to investigate the divergence from the hero’s journey from a director-centric approach towards a navigator-centric approach. Here, the conventional cinema viewer is proposed as a navigator due to the immersive, interactive, and intellectual role they perform in terms of 360-degree viewing, teleportation, and meaning creation. While hero’s journey has been examined across various narrative platforms such as literature, theatre, cinema, gaming, theme parks, education, and more; there are limited discussions on the hero’s journey and its relevance to virtual reality experiences. Table for Two is a one-shot 360-degree audio-visual experience captured simultaneously by three 360-degree cameras. The navigator is encouraged to teleport from one narrative to another as the remaining narratives unfold irrespective of their choices. Each navigator is empowered to untie the knotted pieces and construct a narrative puzzle. Table for Two diverges from the hero’s journey through its multi-linear structure, simultaneous parallel narrative approach, and 360-degree spatial storytelling that offers freedom to navigate.

Innovative K-Means based machine learning method for determination of non-uniform image coordinate system in panoramic imaging: a case study with Ladybug2 camera.

Currently, the practical implementations of panoramic cameras range from vehicle navigation to space studies due to their 360-degree imaging capability in particular. In this variety of uses, it is possible to calculate three-dimensional coordinates from a panoramic image, especially using the Direct Linear Transformation (DLT) method. There are several types of omnidirectional cameras which can be classified mainly as central and non-central cameras for 360-degree imaging. The central omnidirectional cameras are those which satisfy the single-viewpoint characteristic. Multi-camera systems are usually developed for applications for which two-image stereo vision is not flexible enough to capture the environment surrounding a moving platform. Although the technology based on multi-view geometry is inexpensive, accessible, and highly customizable, multi-camera panoramic imaging systems pose a difficulty in obtaining a single projection center for the cameras. In this study, not only a defining method of the non-uniform image coordinate system is suggested by means of the K-Means algorithm for a single panoramic image, captured with a Ladybug2 panoramic camera in the panoramic calibration room but also the use of an elliptical panoramic projection coordinate system definition by Singular Value Decomposition (SVD) method in panoramic view. The results of the suggested method have been compared with the DLT algorithm for a single panoramic image which defined a conventional photogrammetric image coordinate system.

Smart Dairy Farming-The Potential of the Automatic Monitoring of Dairy Cows' Behaviour Using a 360-Degree Camera.

The aim of this study is to show the potential of a vision-based system using a single 360° camera to describe the dairy cows' behaviour in a free-stall barn with an automatic milking system. A total of 2299 snapshots were manually evaluated, counting the number of animals that were lying, standing and eating. The average capture rate of animals in the picture is 93.1% (counted animals/actual numbers of animals). In addition to determining the daily lying, standing and eating times, it is also possible to allocate animals to the individual functional areas so that anomalies such as prolonged standing in the cubicle or lying in the walkway can be detected at an early stage. When establishing a camera monitoring system in the future, attention should be paid to sufficient resolution of the camera during the night as well as the reduction of the concealment problem by animals and barn equipment. The automatic monitoring of animal behaviour with the help of 360° cameras can be a promising innovation in the dairy barn.

RoboCoV Cleaner: An Indoor Autonomous UV-C Disinfection Robot with Advanced Dual-Safety Systems.

In the face of today's ever-evolving global health landscape and ambient assisted living (AAL), marked by the persistent emergence of novel viruses and diseases that impact vulnerable categories and individual safety, the need for innovative disinfection solutions has surged to unprecedented levels. In pursuit of advancing the field of autonomous UV-C disinfection robotics, we conducted two comprehensive state-of-the-art analyses: the first one in the literature and the second one in existing commercial disinfection robots to identify current challenges. Of all of the challenges, we consider the most outstanding ones to be safeguarding humans and animals and understanding the surroundings while operating the disinfection process challenges that we will address in this article. While UV-C lamps have demonstrated their effectiveness in sterilizing air and surfaces, the field of autonomous UV-C disinfection robotics represents a critical domain that requires advancement, particularly in safeguarding the wellbeing of humans and animals during operation. Operating UV-C disinfection robots in close proximity to humans or animals introduces inherent risks, and existing disinfection robots often fall short in incorporating advanced safety systems. In response to these challenges, we propose the RoboCoV Cleaner-an indoor autonomous UV-C disinfection robot equipped with an advanced dual and redundant safety system. This novel approach incorporates multiple passive infrared (PIR) sensors and AI object detection on a 360-degree camera. Under our test, the dual-redundant system reached more than 90% when detecting humans with high accuracy using the AI system 99% up to 30 m away in a university hallway (different light conditions) combined with the PIR system (with lower accuracy). The PIR system was proved to be a redundant system for uninterrupted operation during communication challenges, ensuring continuous sensor information collection with a swift response time of 50 ms (image processing within 200 ms). It empowers the robot to detect and react to human presence, even under challenging conditions, such as when individuals wear masks, in complete darkness, under UV light, or in environments with blurred visual conditions. In our test, the detection system performed outstandingly well with up to 99% detection rate of humans. Beyond safety features, the RoboCoV Cleaner can identify objects in its surroundings. This capability empowers the robot to discern objects affected by UV-C light, enabling it to apply specialized rules for targeted disinfection. The proposed system exhibits a wide range of capabilities beyond its core purpose of disinfection, making it suitable for healthcare facilities, universities, conference venues, and hospitals. Its implementation has the ability to improve significantly human safety and protect people. By showcasing the RoboCoV Cleaner's safety-first approach and adaptability, we aim to set a new benchmark for UV-C disinfection robots, promoting clean and secure environments while protecting vulnerable people, even in challenging scenarios.

Generating Mobile Virtual Tour Using UAV and 360 Degree Panorama for Geography-Environmental Learning in Higher Educationw

Nowadays, the limitations of media in geo-environmental learning present a significant challenge, as media plays an indispensable role in fostering students’ comprehensive understanding. Employing technology capable of delivering comprehensive landscape information is crucial for effective environmental education. Utilizing Unmanned Aerial Vehicles (UAVs) and 360-degree panoramic cameras represents a judicious technological choice, which can be seamlessly integrated into virtual tours. This research aims to develop a Mobile Virtual Tour (Movie-Tour) as a medium to support learning, especially for materials regarding environmental geography. The research and development (RnD) method is used in research with the ADDIE model (Analysis, Design, Development, Implementation and Evaluation). Data collection for the development of the product involved conducting a need assessment, performing validation tests and conducting trials with students. To gather field data for creating environmental geography materials for the Movie-Tour product, we utilized an Unmanned Aerial Vehicle (UAV) and a 360-degree stereoscopic camera. The results demonstrate that Movie- Tour is an educational medium capable of delivering an immersive learning experience and comprehensive materials, allowing for the virtual visualization of real-world conditions in the field. This capability enhances students’ engagement in exploring physical geography conditions, fosters independent knowledge acquisition, and nurtures their innate curiosity. Movie-Tour stands as a potent and practical educational tool, offering an effective and secure learning experience for students, eliminating the need for direct field visits.

A NiO@Ti based linear photoelectrochemical type ultraviolet photodetector

Omnidirectional detection is widely used in optical tracking systems, omni-directional cameras and optical field measurements and so on. However, the planar structures of ultraviolet (UV) photodetectors (PDs) limit their application in omnidirectional detection. In this work, the NiO nanosheets were fabricated on a titanium (Ti) wire substrate by hydrothermal method and then assembled a photoelectrochemical (PEC) type UV photodetector (PD). Under ultraviolet (UV) irradiation of 35 mW cm−2 @ 365 nm, the PD exhibits a stable photocurrent of 1.53 μA cm−2 and repeatable switching cycles. Also, the PD presents fast response and recovery times of 0.074 s and 0.130 s, respectively. Particularly, the PD based on NiO@Ti possesses excellent response for rotation angles in the range from 0° to 360° under UV light irradiation.