Augmented Reality Tasks Research Articles

Understanding Gesture and Speech Multimodal Interactions for Manipulation Tasks in Augmented Reality Using Unconstrained Elicitation

This research establishes a better understanding of the syntax choices in speech interactions and of how speech, gesture, and multimodal gesture and speech interactions are produced by users in unconstrained object manipulation environments using augmented reality. The work presents a multimodal elicitation study conducted with 24 participants. The canonical referents for translation, rotation, and scale were used along with some abstract referents (create, destroy, and select). In this study time windows for gesture and speech multimodal interactions are developed using the start and stop times of gestures and speech as well as the stoke times for gestures. While gestures commonly precede speech by 81 ms we find that the stroke of the gesture is commonly within 10 ms of the start of speech. Indicating that the information content of a gesture and its co-occurring speech are well aligned to each other. Lastly, the trends across the most common proposals for each modality are examined. Showing that the disagreement between proposals is often caused by a variation of hand posture or syntax. Allowing us to present aliasing recommendations to increase the percentage of users' natural interactions captured by future multimodal interactive systems.

Alterations in surface EMG during gait in children with Fragile X Syndrome

This study aimed to characterize the biomechanical stresses in the neck and shoulder, self-reported discomfort, and usability by different target distance or size during augmented reality (AR) interactions. In a repeated-measures laboratory-based study, 20 participants (10 males) performed three standardized AR tasks (3-dimensional (3-D) cube, omni-directional pointing, and web-browsing tasks) with three target distances (0.3, 0.6, and 0.9 m from each participant denoted by near, middle, far targets) for the 3-D cube and omni-directional pointing tasks or three target sizes: small (30% smaller than default), medium (default: 1.0 × 1.1 m), and large (30% larger than default) for the web-browsing task. Joint angle, joint moment, muscle activity, self-reported discomfort and comfort in the neck and shoulders; and subjective usability ratings were measured. The results showed that shoulder angle (flexion and abduction), shoulder moment (flexion), middle deltoid muscle activity significantly increased as the target distance increased during the 3-D cube task (p's < 0.001). Self-reported neck and shoulder discomfort significantly increased after completing each task (p's < 0.001). The participants preferred the near to middle distance (0.3–0.6 m) or the medium to large window size due to task easiness (p's < 0.005). The highest task performance (speed) was occurred at the near distance or the large window size during the 3-D cube and web-browsing tasks (p's < 0.001). The results indicate that AR interactions with the far target distance (close to maximum reach envelop) may increase the risk for musculoskeletal discomfort in the shoulder regions. Given the increased usability and task performance, the near to middle distance (less than 0.6 m) or the medium to large window size (greater than 1.0 × 1.1 m) would be recommended for AR interactions.

Individualized Augmented Reality Training Reduces Phantom Pain and Cortical Reorganization in Amputees: A Proof of Concept Study

Phantom limb pain (PLP) may be relieved using a visual representation of an intact limb. However, patients with distorted (telescoped) phantoms seem unable to associate with visualizations of intact limbs. A virtual arm visualization was matched to the individual's phantom perception and controlled in an augmented reality (AR) intervention. Seven PLP participants with telescoped phantoms performed 8 supervised home-based AR-training sessions (45 minutes each) within 2 weeks. The virtual arm was superimposed in AR onto their residual limb and controlled using electromyography from the residual limb. AR-training sessions included 3 AR tasks aimed at reengaging the neural circuits related to the lost limb. Agency (Rubber hand illusion questionnaire) and telescoping (proprioceptive drift and felt telescoping) were monitored after individual training sessions. fMRI during lip pursing was assessed before and after intervention. Pain rating index scores were reduced by 52% (mean change = −1.884, P = .032, d = 1.135). Numerical rating scale scores of PLP severity (0–6) in patients benefitting from the intervention were reduced by 41% (mean change = .93 P = .022, d = 1.334). The lip pursing task illustrated decreased cortical activity in the primary somatosensory cortex, which correlated to the reduced numerical rating scale scores of PLP severity. PerspectiveTwo weeks of novel AR interventions in patients with telescoped phantoms demonstrated reduced PLP and reversal of cortical reorganization. This research highlights the potential of individualized AR interventions for PLP and indicate the importance of agency in this type of treatments.

Evaluation of the biomechanical stress in the neck and shoulders during augmented reality interactions

This study aimed to characterize the biomechanical stresses in the neck and shoulder, self-reported discomfort, and usability by different target distance or size during augmented reality (AR) interactions. In a repeated-measures laboratory-based study, 20 participants (10 males) performed three standardized AR tasks (3-dimensional (3-D) cube, omni-directional pointing, and web-browsing tasks) with three target distances (0.3, 0.6, and 0.9 m from each participant denoted by near, middle, far targets) for the 3-D cube and omni-directional pointing tasks or three target sizes: small (30% smaller than default), medium (default: 1.0 × 1.1 m), and large (30% larger than default) for the web-browsing task. Joint angle, joint moment, muscle activity, self-reported discomfort and comfort in the neck and shoulders; and subjective usability ratings were measured. The results showed that shoulder angle (flexion and abduction), shoulder moment (flexion), middle deltoid muscle activity significantly increased as the target distance increased during the 3-D cube task (p's < 0.001). Self-reported neck and shoulder discomfort significantly increased after completing each task (p's < 0.001). The participants preferred the near to middle distance (0.3–0.6 m) or the medium to large window size due to task easiness (p's < 0.005). The highest task performance (speed) was occurred at the near distance or the large window size during the 3-D cube and web-browsing tasks (p's < 0.001). The results indicate that AR interactions with the far target distance (close to maximum reach envelop) may increase the risk for musculoskeletal discomfort in the shoulder regions. Given the increased usability and task performance, the near to middle distance (less than 0.6 m) or the medium to large window size (greater than 1.0 × 1.1 m) would be recommended for AR interactions.

Seeing other perspectives: evaluating the use of virtual and augmented reality to simulate visual impairments (OpenVisSim)

Simulations of visual impairment are used to educate and inform the public. However, evidence regarding their accuracy remains lacking. Here we evaluated the effectiveness of modern digital technologies to simulate the everyday difficulties caused by glaucoma. 23 normally sighted adults performed two everyday tasks that glaucoma patients often report difficulties with: a visual search task in which participants attempted to locate a mobile phone in virtual domestic environments (virtual reality (VR)), and a visual mobility task in which participants navigated a physical, room-scale environment, while impairments were overlaid using augmented reality (AR). On some trials, a gaze-contingent simulated scotoma—generated using perimetric data from a real patient with advanced glaucoma—was presented in either the superior or inferior hemifield. The main outcome measure was task completion time. Eye and head movements were also tracked and used to assess individual differences in looking behaviors. The results showed that the simulated impairments substantially impaired performance in both the VR (visual search) and AR (visual mobility) tasks (both P < 0.001). Furthermore, and in line with previous patient data: impairments were greatest when the simulated Visual Field Loss (VFL) was inferior versus superior (P < 0.001), participants made more eye and head movements in the inferior VFL condition (P < 0.001), and participants rated the inferior VFL condition as more difficult (P < 0.001). Notably, the difference in performance between the inferior and superior conditions was almost as great as the difference between a superior VFL and no impairment at all (VR: 71%; AR: 70%). We conclude that modern digital simulators are able to replicate and objectively quantify some of the key everyday difficulties associated with visual impairments. Advantages, limitations, and possible applications of current technologies are discussed. Instructions are also given for how to freely obtain the software described (OpenVisSim).

Use of Augmented Reality with a Motion-Controlled Game Utilizing Alphabet Letters and Numbers to Improve Performance and Reaction Time Skills for People with Autism Spectrum Disorder.

Augmented reality (AR) uses the real-world setting but enables a person to interact with virtual objects. In this study, we aimed to explore the use of alphabet letter and number in an AR task and its influence in reaction time in a population with autism spectrum disorders (ASD) compared with the performance of typical developing (TD) controls. We evaluated reaction time before and after AR tasks that consisted of identifying correct numbers and alphabet letters in 48 people with ASD and 48 with TD controls. Results indicate that total points for TD group were higher (M = 86.4 and M = 79.0) when compared with the ASD group (M = 54.5 and M = 51.5) for alphabet letters and numbers, respectively. Moreover, in analysis of reaction time results, only the ASD group showed an improvement in performance after the practice of an AR task. The control group was faster before (M = 553.7) and after (M = 560.5) when compared with the ASD group (M = 2616.0 and M = 2374.6, respectively). Despite the need for further studies, our results support that there is potential for clinical use of an AR task-based intervention for people with ASD.

EEG-Based Classification of Internally- and Externally-Directed Attention in an Augmented Reality Paradigm.

One problem faced in the design of Augmented Reality (AR) applications is the interference of virtually displayed objects in the user's visual field, with the current attentional focus of the user. Newly generated content can disrupt internal thought processes. If we can detect such internally-directed attention periods, the interruption could either be avoided or even used intentionally. In this work, we designed a special alignment task in AR with two conditions: one with externally-directed attention and one with internally-directed attention. Apart from the direction of attention, the two tasks were identical. During the experiment, we performed a 16-channel EEG recording, which was then used for a binary classification task. Based on selected band power features, we trained a Linear Discriminant Analysis classifier to predict the label for a 13-s window of each trial. Parameter selection, as well as the training of the classifier, were done in a person-dependent manner in a 5-fold cross-validation on the training data. We achieved an average score of approximately 85.37% accuracy on the test data (± 11.27%, range = [66.7%, 100%], 6 participants > 90%, 3 participants = 100%). Our results show that it is possible to discriminate the two states with simple machine learning mechanisms. The analysis of additionally collected data dispels doubts that we classified the difference in movement speed or task load. We conclude that a real-time assessment of internal and external attention in an AR setting in general will be possible.

Memory for Object Location in Augmented Reality: The Role of Gender and the Relationship Among Spatial and Anxiety Outcomes.

The potential of augmented reality (AR) technology for the study of spatial memory and orientation is a new research field. AR defines systems that attempt to enhance the user’s experience with the physical world. In our app, we enhance the sense of sight by adding interactive 3D elements to the real environment. Our app can be used in any real environment so that the experimental conditions during the tasks and the way in which an individual navigates are similar to those used in real life. With AR, the experimenter has a high level of control of the task and can store the participant’s responses accurately. The classical factors that influence an individual’s performance on virtual spatial tasks are gender and cognitive factors. The influence of emotional factors on spatial performance has been studied more recently. Since AR tasks for the study of spatial memory and spatial orientation are new developments, little is known about the factors that are related to performance on tasks of this type. In our study, we tested 46 young adults (26 women) in an AR object-location task that was performed in a building. The participants had to memorize the position of eight virtual objects while they were walking through the environment. We also assessed the participants’ performance on an object-recall task, a map-pointing task, and a paper-and-pencil spatial orientation task. The self-reported importance of different spatial strategies for wayfinding and the levels of trait anxiety and wayfinding anxiety were also evaluated. Our findings indicate that men performed better on the spatial paper-and-pencil test and spent more time completing the learning phase of the AR task. The spatial memory for the location of the objects in AR and on the map correlated positively. Anxiety was related to individual differences in the self-reported use of a spatial orientation strategy, but the association among them was weak. Trait anxiety was positively related to the time employed by the participants during the learning phase of the AR task, whereas wayfinding anxiety correlated negatively with the preference for an orientation strategy. Our results highlight the importance of anxiety in spatial orientation.

Code-Partitioning Offloading Schemes in Mobile Edge Computing for Augmented Reality

Augmented reality (AR) is one of the emerging use cases relying on ultra-reliable and low-latency communications (uRLLC). The AR service is composed of multiple dependent computational-intensive components. Due to the limited capability of user equipment (UE), it is difficult to meet the stringent latency and reliability requirements of AR service merely by local processing. To solve the problem, it is viable to offload parts of the AR task to the network edge, i.e., mobile edge computing (MEC), which is expected to extend the computing capability of the UE. However, MEC also incurs extra communication latency and errors on the wireless channel; therefore, it is challenging to make an optimum offload decision. So far, a little of state-of-the-art work has considered both the latency and reliability of the MEC-enabled AR service. In this paper, we study the scenario multiple edge nodes cooperate to complete the AR task. The dependency of task components is modeled by a directed acyclic graph through code partitioning. We aim to minimize the service failure probability (SFP) of the MEC-enabled AR service considering reliability and latency. We design an integer particle swarm optimization (IPSO)-based algorithm. Although the solution of IPSO-based algorithm approaches the optimum of the problem, it is infeasible to use IPSO for real-time AR services in practice due to the relatively high computational complexity. Hence, we propose a heuristic algorithm, which achieves a performance close to that of the IPSO-based algorithm with much lower complexity. Compared with state-of-the-art work, the heuristic algorithm can significantly improve the probability to fulfill the targeted SFP in various network conditions. Due to the generic characteristics, the proposed heuristic algorithm is applicable for AR services, as well as for many other use cases in uRLLC.

CATCHA: Real-Time Camera Tracking Method for Augmented Reality Applications in Cultural Heritage Interiors

Camera pose tracking is a fundamental task in Augmented Reality (AR) applications. In this paper, we present CATCHA, a method to achieve camera pose tracking in cultural heritage interiors with rigorous conservatory policies. Our solution is real-time model-based camera tracking according to textured point cloud, regardless of its registration technique. We achieve this solution using orthographic model rendering that allows us to achieve real-time performance, regardless of point cloud density. Our developed algorithm is used to create a novel tool to help both cultural heritage restorers and individual visitors visually compare the actual state of a culture heritage location with its previously scanned state from the same point of view in real time. The provided application can directly achieve a frame rate of over 15 Hz on VGA frames on a mobile device and over 40 Hz using remote processing. The performance of our approach is evaluated using a model of the King’s Chinese Cabinet (Museum of King Jan III’s Palace at Wilanów, Warsaw, Poland) that was scanned in 2009 using the structured light technique and renovated and scanned again in 2015. Additional tests are performed on a model of the Al Fresco Cabinet in the same museum, scanned using a time-of-flight laser scanner.

Predictive trajectory estimation during rehabilitative tasks in augmented reality using inertial sensors.

This paper presents a wireless kinematic tracking framework used for biomechanical analysis during rehabilitative tasks in augmented and virtual reality. The framework uses low-cost inertial measurement units and exploits the rigid connections of the human skeletal system to provide egocentric position estimates of joints to centimeter accuracy. On-board sensor fusion combines information from three-axis accelerometers, gyroscopes, and magnetometers to provide robust estimates in real-time. Sensor precision and accuracy were validated using the root mean square error of estimated joint angles against ground truth goniometer measurements. The sensor network produced a mean estimate accuracy of 2.81° with 1.06° precision, resulting in a maximum hand tracking error of 7.06 cm. As an application, the network is used to collect kinematic information from an unconstrained object manipulation task in augmented reality, from which dynamic movement primitives are extracted to characterize natural task completion in N = 3 able-bodied human subjects. These primitives are then leveraged for trajectory estimation in both a generalized and a subject-specific scheme resulting in 0.187 cm and 0.161 cm regression accuracy, respectively. Our proposed kinematic tracking network is wireless, accurate, and especially useful for predicting voluntary actuation in virtual and augmented reality applications.

Combining Wearable Finger Haptics and Augmented Reality: User Evaluation Using an External Camera and the Microsoft HoloLens

Augmented reality (AR) enriches our physical world with digital content and media, such as three-dimensional models and videos, overlaying in real time the camera view of our smartphone, tablet, laptop, or glasses. Despite the recent massive interest for this technology, it is still not possible to receive rich haptic feedback when interacting with augmented environments. This lack is mainly due to the poor diffusion of suitable haptic interfaces, which should be easy to wear, lightweight, compact, and inexpensive. In this letter, we briefly review the state of the art on wearable haptics and its application in AR. Then, we present three AR use cases, considering tasks of manipulation, guidance, and gaming, using both external cameras with standard screens as well as fully wearable solutions, using the Microsoft HoloLens. We evaluate these tasks enrolling a total of 34 subjects, analyzing performance and user experience when using a 3-DoF wearable device for the fingertip, a 2-DoF wearable device for the proximal finger phalanx, a vibrotactile ring, and a popular sensory substitution technique (interaction force displayed as a colored bar). Results show that providing haptic feedback through the wearable devices significantly improves the performance, intuitiveness, and comfort of the considered AR tasks.

Improved frame-by-frame object pose tracking in complex environments

Pose tracking is an important task in Augmented Reality (AR), interactive systems, and robotic systems. The frame-by-frame pose tracking that is effective in many cases still faces challenges in complex environments such as occlusions, illumination changes and flipping. In this paper, based on the optimization model offered by Ye et al. J Vis Commun Image Represent 44:72–81 (2017), three improvements are further proposed. First, a feature adjustment strategy based on a group of neighbors is offered to alleviate a sharp reduction of features. Then, when the features are no longer well representing the scene of interest, a score model based on a weighted histogram for result evaluations is presented to realize an adaptive interval. Besides, a forward-backward algorithm is provided to improve the accuracy by replacing the detection method with the tracking method. Experimental results manifest the effectiveness of the proposed algorithms.

Learning in the navigational space: Age differences in a short-term memory for objects task

Age differences during development in visuospatial short-term memory (VSTM) in navigation have not been sufficiently proven. The performance of typically developing children from five age groups (from 5 to 9years old) and one group of young adults (from 25 to 30years old) was studied in an Augmented Reality navigational VSTM task that involved remembering the location of objects presented in increasing span lengths. The main results showed that navigational VSTM has not fully developed at the age of 9. The measures of performance significantly improved between ages 8 and 9. The overall performance on our navigational task was not influenced by gender, but there was a slight advantage for males when the difficulty of the task increased regarding the performance accuracy and the errors committed. The Augmented Reality task correlated with traditional spatial tests. Possible cognitive, biological, and methodological explanations for the findings are discussed.

Augmented reality for the assessment of children's spatial memory in real settings.

Short-term memory can be defined as the capacity for holding a small amount of information in mind in an active state for a short period of time. Although some instruments have been developed to study spatial short-term memory in real environments, there are no instruments that are specifically designed to assess visuospatial short-term memory in an attractive way to children. In this paper, we present the ARSM (Augmented Reality Spatial Memory) task, the first Augmented Reality task that involves a user's movement to assess spatial short-term memory in healthy children. The experimental procedure of the ARSM task was designed to assess the children's skill to retain visuospatial information. They were individually asked to remember the real place where augmented reality objects were located. The children (N = 76) were divided into two groups: preschool (5–6 year olds) and primary school (7–8 year olds). We found a significant improvement in ARSM task performance in the older group. The correlations between scores for the ARSM task and traditional procedures were significant. These traditional procedures were the Dot Matrix subtest for the assessment of visuospatial short-term memory of the computerized AWMA-2 battery and a parent's questionnaire about a child's everyday spatial memory. Hence, we suggest that the ARSM task has high verisimilitude with spatial short-term memory skills in real life. In addition, we evaluated the ARSM task's usability and perceived satisfaction. The study revealed that the younger children were more satisfied with the ARSM task. This novel instrument could be useful in detecting visuospatial short-term difficulties that affect specific developmental navigational disorders and/or school academic achievement.

A novel augmented reality simulator for skills assessment in minimal invasive surgery.

Over the past decade, simulation-based training has come to the foreground as an efficient method for training and assessment of surgical skills in minimal invasive surgery. Box-trainers and virtual reality (VR) simulators have been introduced in the teaching curricula and have substituted to some extent the traditional model of training based on animals or cadavers. Augmented reality (AR) is a new technology that allows blending of VR elements and real objects within a real-world scene. In this paper, we present a novel AR simulator for assessment of basic laparoscopic skills. The components of the proposed system include: a box-trainer, a camera and a set of laparoscopic tools equipped with custom-made sensors that allow interaction with VR training elements. Three AR tasks were developed, focusing on basic skills such as perception of depth of field, hand-eye coordination and bimanual operation. The construct validity of the system was evaluated via a comparison between two experience groups: novices with no experience in laparoscopic surgery and experienced surgeons. The observed metrics included task execution time, tool pathlength and two task-specific errors. The study also included a feedback questionnaire requiring participants to evaluate the face-validity of the system. Between-group comparison demonstrated highly significant differences (<0.01) in all performance metrics and tasks denoting the simulator's construct validity. Qualitative analysis on the instruments' trajectories highlighted differences between novices and experts regarding smoothness and economy of motion. Subjects' ratings on the feedback questionnaire highlighted the face-validity of the training system. The results highlight the potential of the proposed simulator to discriminate groups with different expertise providing a proof of concept for the potential use of AR as a core technology for laparoscopic simulation training.

Experimenting with electromagnetism using augmented reality: Impact on flow student experience and educational effectiveness

Educational researchers have recognized Augmented Reality (AR) as a technology with great potential to impact affective and cognitive learning outcomes. However, very little work has been carried out to substantiate these claims. The purpose of this study was to assess to which extent an AR learning application affects learners' level of enjoyment and learning effectiveness. The study followed an experimental/control group design using the type of the application (AR-based, web-based) as independent variable. 64 high school students were randomly assigned to the experimental or control group to learn the basic principles of electromagnetism. The participants' knowledge acquisition was evaluated by comparing pre- and post-tests. The participants' level overall-state perception on flow was measured with the Flow State Scale and their flow states were monitored throughout the learning activity. Finally, participants' perceptions of benefits and difficulties of using the augmented reality application in this study were qualitatively identified. The results showed that the augmented reality approach was more effective in promoting students' knowledge of electromagnetic concepts and phenomena. The analysis also indicated that the augmented reality application led participants to reach higher flow experience levels than those achieved by users of the web-based application. However, not all the factors seem to have influence on learners' flow state, this study found that they were limited to: concentration, distorted sense of time, sense of control, clearer direct feedback, and autotelic experience. A deeper analysis of the flow process showed that neither of the groups reported being in flow in those tasks that were very easy or too difficult. However, for those tasks that were not perceived as difficult and included visualization clues, the experimental group showed higher levels of flow that the control group. The study suggests that augmented reality can be exploited as an effective learning environment for learning the basic principles of electromagnetism at high school provided that learning designers strike a careful balance between AR support and task difficulty.

The Effects of Visual Realism on Search Tasks in Mixed Reality Simulation

In this paper, we investigate the validity of Mixed Reality (MR) Simulation by conducting an experiment studying the effects of the visual realism of the simulated environment on various search tasks in Augmented Reality (AR). MR Simulation is a practical approach to conducting controlled and repeatable user experiments in MR, including AR. This approach uses a high-fidelity Virtual Reality (VR) display system to simulate a wide range of equal or lower fidelity displays from the MR continuum, for the express purpose of conducting user experiments. For the experiment, we created three virtual models of a real-world location, each with a different perceived level of visual realism. We designed and executed an AR experiment using the real-world location and repeated the experiment within VR using the three virtual models we created. The experiment looked into how fast users could search for both physical and virtual information that was present in the scene. Our experiment demonstrates the usefulness of MR Simulation and provides early evidence for the validity of MR Simulation with respect to AR search tasks performed in immersive VR.

Real-Time Tracking Error Estimation for Augmented Reality for Registration with Linecode Markers

Augmented reality tasks require a high-reliability tracking method. Large tracking error causes many problems during AR applications. Tracking error estimation should be integrated with them to improve the reliability of tracking methods. Although some tracking error estimation methods have been developed, they are not feasible to be integrated because of computational speed and accuracy. For this study, a tracking error estimation algorithm with screen error estimation based on the characteristic of linecode marker was applied. It can rapidly estimate tracking error. An evaluation experiment was conducted to compare the estimated tracking error and the actual measured tracking error. Results show that the algorithm is reliable and sufficiently fast to be used for real-time tracking error warning or tracking accuracy improvement methods.

A hybrid tracking method for surgical augmented reality

Camera pose estimation is one of the most important, but also one of the most challenging tasks in augmented reality. Without a highly accurate estimation of the position and orientation of the digital video camera, it is impossible to render a spatially correct overlay of graphical information. This requirement is even more crucial in medical applications, where virtual objects typically have to be correctly aligned with the patient. Many experimental AR systems use specialized tracking devices, which usually are not certified for medical settings. We have developed an AR framework for surgical applications based on existing medical equipment. A surgical navigation device delivers tracking information measured by a built-in infrared camera system, which is the basis for the pose estimation of the AR video camera. However, depending on the conditions in the environment, this infrared pose data can contain discernible tracking errors. One main drawback of the medical tracking device is the fact that, while it delivers a very high positional accuracy, the reported camera orientation can contain a relatively large error. In this article, we present a hybrid tracking scheme for medical augmented reality based on a certified medical tracking system. The final pose estimation takes the initial infrared tracking data as well as salient features in the camera image into account. The vision-based component of the tracking algorithm relies on a pre-defined graphical model of the observed scene. The infrared and vision-based tracking data are tightly integrated into a unified pose estimation algorithm. This algorithm is based on an iterative numerical optimization method. We describe an implementation of the algorithm and present experimental data showing that our new method is capable of delivering a more accurate pose estimation.