Extended reality (XR) technologies are transforming domains like gaming, healthcare, and training, offering benefits such as enhanced safety, cost reduction, and immersive experiences. However, current XR systems often overlook accessibility for individuals with diverse abilities and remain unexplored in inclusive learning contexts. The Incluverso-5G project seeks to address this gap by leveraging XR to improve the lives of individuals with intellectual disabilities, including employment inclusion. This paper presents an immersive tool to support remote training for certified cooking courses, enabling users unable to attend in-person classes to access training and certification.The system includes an advanced 360-degree content viewer and a real-time immersive supervision tool, utilizing features like six degrees of freedom (6-DoF), color passthrough, and hand tracking for interactive learning. A four-step remote learning process—sensitization, instructional content, supervised practice, and certification—ensures accessibility and usability. The tool empowers individuals to acquire valuable skills and achieve professional certifications, demonstrating the potential of XR for inclusive training.

Cognitive training is a common therapeutic approach to improve the quality of life of individuals with intellectual disabilities, although conventional methods often show limited engagement and skill transfer. The use of eXtended Reality (XR) allows to develop immersive cognitive training, with evidence of improved motivation and engagement. In parallel, biosignals and behavioral metrics are increasingly used to assess user experience and cognitive state in immersive environments. This study presents a longitudinal evaluation of an immersive cognitive training application involving eight participants over eight months. Multiple data sources were collected, including eye tracking, electromyography and electrodermal activity, together with questionnaires and interviews to capture subjective experience. Preliminary results focus on gaze and interaction data. The number of fixations reflects task complexity, with more complex scenarios associated with increased exploratory behavior and a higher proportion of fixations on distracting elements. Interaction data from the most complex task indicate improved efficiency over time both before and during actions. Further analysis will explore these findings and incorporate the remaining physiological and behavioral data, together with the analysis of the interviews and questionnaires.

This paper presents one of the first studies on estimating group emotional states in immersive communication environments. We designed a two-phase experiment to assess group emotion recognition in both controlled and natural settings. In the forced-emotion phase, 32 participants mimicked predefined emotions in 2D and 360° video. In the natural-emotion phase, the OpenLAV dataset elicited stronger and more diverse affective responses than LIRIS-ACCEDE, indicating better suitability for triggering emotions. We also found that neutral states are mostly detected as slightly negative valence, suggesting a systematic bias in affect estimation. The study also found greater variability in valence than in arousal, potentially due to the professional setting of the experiment. Overall, the findings demonstrate the feasibility of coarse group emotion detection in 360° video showing a high correlation with participants’ self-perceptions. We believe this tool could be useful for making immersive communication more effective for audience monitoring, enhancing presentation skills, but also more inclusive for people with emotion understanding difficulties.

Embodied design can be an effective approach for developing extended reality (XR) experiences by enabling design teams to ideate and prototype through hands-on physical interaction. This body-centric approach is particularly valuable for addressing the complexities and paradigm shifts inherent in XR systems, where users engage significantly with their bodies in virtual environments, i.e. through head movements, body orientation, and hand tracking among others. In this paper, we present an embodied design method, which we used to design an XR-based cooking learning tool aimed at fostering autonomous learning for individuals with intellectual disabilities. The learning tool features 360-degree video recipes with a configurable combination of immersive video and passthrough views to adapt to different user needs and contexts. Our method includes functional prototypes to iterate current design concepts and explore usability across different possible interaction modalities. These tools were used to implement the Wizard of Oz technique and simulate different interaction techniques-such as voice commands and simple button-based inputs. To assess the usability of these tools, we employed the subjective Quality of Experience (QoE) assessment. The inclusion of this form of evaluation directly within the embodied design process is a novel contribution, providing valuable information about the usability of the prototypes as embodied design tools. Finally, we present preliminary results of the workshop, which illustrate the usefulness of embodied design for the development of XR interactive experiences.

Emerging fields like TeleOperated Driving (ToD) need to assess video quality for remote video transmission at different network available bitrates facing complexity challenges. This paper presents a novel dataset to contribute to the development of tailored quality metrics for ToD. Existing state-of-the-art AI detection algorithms and video quality metrics have been applied to a curated selection of sequences from existing self-driving video datasets, reencoded at different bitrates, thus generating a new dataset and the required tools to replicate the results. A correlation study of video quality and object detection metrics is also presented. Preliminary results show that state-of-the-art video quality metrics provide limited correlation with driving task performance, evaluated as degradation of detection of key objects and regions. The generated dataset and the framework to encode the video and obtain the measurements are publicly available at https://github.com/nachobfrupm/TOD_QualityVideoEncoding

The popularity of short-form video requires careful planning by service providers and network operators aiming to deliver high Quality of Experience (QoE) while minimizing bandwidth wastage from excessive preloading and unpredictable swiping behavior. Service providers utilize preloading strategies to optimize these trade-offs against their target metrics. In this work, we introduce a Markov model that estimates key quality indicators (KQIs) and bandwidth wastage for common preloading strategies, network conditions, and swiping behaviors. We compare two preloading strategies and show that the number of preloaded segments per video results in a trade-off between initial delay and stalling. Further, we highlight the key impact of swiping behavior on both KQIs and bandwidth wastage.

The increasing deployment of immersive technologies is opening up opportunities in the field of behavioral therapies.In particular, the use of eXtended Reality technologies allows the development of therapies that require bringing users to a remote location without

The combination of eXtended Reality (XR) technologies with physiological signals offers innovative approaches to cognitive training for individuals with intellectual disabilities.This study presents a tool designed for cognitive training aimed at job integration through interactive and immersive environments.The tool was developed in collaboration with therapists from the Juan XXIII Foundation, an occupational center, and focuses on enhancing cognitive skills through serious games for job training.These games simulate realistic environments, such as a cafeteria and a supermarket, where users must complete various tasks.These tasks are designed to progressively increase in complexity as users advance, allowing them to improve their skills.Therapists can monitor and control the training sessions in real-time through an application, while users engage with the immersive scenarios.Additionally, the system incorporates non-invasive biosensors to track physiological data, such as heart rate, eye movement, etc. providing valuable insights into the

Network and service providers actively analyze and derive metrics for Quality of Experience (QoE) within their systems. This requires appropriate monitoring approaches. Objective QoE monitoring involves translating QoS parameters into QoE scores by applying appropriate mapping functions, e.g., to obtain Mean Opinion Scores (MOS). Alternatively, individual QoE monitoring allows direct assessment of user QoE based on user’s self-reports. We investigate whether individual and objective QoE monitoring yield similar conclusions on expected QoE and QoE fairness. A theoretical framework is introduced and simulation studies provide numerical results to highlight the differences. This is the first work which analyzes and compares individual and objective QoE monitoring from the provider’s perspective. It closes a major gap in the current QoE research.

Extended reality has generated great interest in recent years, among other things, due to the potential it has to transmit non-verbal communication and offer solutions to current distancing problems. This work proposes a gamified experience of three use cases that meet real-life scenarios: teleassistance, guided route, and remote technical support. The objective is to solve each of the scenario tasks that involve collaboration between local and remote users through 360-degree video communication. Specifically, 2D and 3D objects hide symbols that local users must decipher with the help of remote users, who have the necessary information to do that. In this way, the technology (360-degree video communication) and additional tools included in the system are tested: a magnifying glass to offer remote users certain areas of the scene with higher quality, visualization of the hands with the headset to make the experience more realistic, and the cartoon avatars to increase perceived social presence during the interaction. This experience considers the needs of real hybrid meeting applications that have been gamified to test 360-degree video communication but apply to other XR technologies.

This paper evaluates a virtual teleportation system based on 360-degree video communication in a field study at a secondary school and a guided debate training session. Socioemotional aspects, including social presence and avatar representation, were assessed by eight teens. Key findings include a higher "wow" effect for those joining the immersive environment, and challenges with avatar interaction such as raising their hand. The system shows promise as an educational tool for debate training and student engagement.

In recent years, advances in immersive multimedia technologies, such as extended reality (XR) technologies, have led to more realistic and user-friendly devices. However, these devices are often bulky and uncomfortable, still requiring tether connectivity for demanding applications. The deployment of the fifth generation of telecommunications technologies (5G) has set the basis for XR offloading solutions with the goal of enabling lighter and fully wearable XR devices. In this paper, we present a traffic dataset for two demanding XR offloading scenarios that substantially extend those available in the current state of the art, captured using a fully developed end-to-end XR offloading solution. We also propose a set of accurate traffic models for the proposed scenarios based on the captured data, accompanied by a simple and consistent method to generate synthetic data from the fitted models. Finally, using an open-source 5G radio access network (RAN) emulator, we validate the models both at the application and resource allocation layers. Overall, this work aims to provide a valuable contribution to the field with data and tools for designing, testing, improving, and extending XR offloading solutions in academia and industry.

Immersive technologies like eXtended Reality (XR) are the next step in videoconferencing. In this context, understanding the effect of delay on communication is crucial. This article presents the first study on the impact of delay on collaborative tasks using a realistic Social XR system. Specifically, we design an experiment and evaluate the impact of end-to-end delays of 300, 600, 900, 1,200, and 1,500 ms on the execution of a standardized task involving the collaboration of two remote users that meet in a virtual space and construct block-based shapes. To measure the impact of the delay in this communication scenario, objective and subjective data were collected. As objective data, we measured the time required to execute the tasks and computed conversational characteristics by analyzing the recorded audio signals. As subjective data, a questionnaire was prepared and completed by every user to evaluate different factors such as overall quality, perception of delay, annoyance using the system, level of presence, cybersickness, and other subjective factors associated with social interaction. The results show a clear influence of the delay on the perceived quality and a significant negative effect as the delay increases. Specifically, the results indicate that the acceptable threshold for end-to-end delay should not exceed 900 ms. This article additionally provides guidelines for developing standardized XR tasks for assessing interaction in Social XR environments.

This paper presents a comparison between three content-immersive methodologies to evaluate video quality: Absolute Category Rating (ACR) with unrepeated scenes, Single Stimulus Continuous Quality Evaluation (SSCQE), and Single Stimulus Discrete Quality Evaluation (SSDQE). Three tests were conducted with different participants assigned to each methodology to assess 360-degree video quality in an immersive communications context. Additionally, socioemotional aspects such as presence, attitude, or attention were measured for each condition. All three methodologies offer similar results in terms of video quality evaluation, and they all keep similar levels of social and spatial presence. Both SSCQE and SSDQE allow narrative and context while evaluating video quality, but SSDQE has less impact in participants' attention to the video content. These results suggest that it is possible to extend ITU-T P.919 with the support of long sequences with in-sequence SSDQE video quality evaluation, without significant impact on the socioemotional properties of the experience. This would result on a standard content-immersive method, methodology suitable for 360-degree video content, favoring the ecological validity of the subjective assessment tests.

Parametric planning models provide an estimation of the perceived Quality of Experience (QoE) for a certain set of values of relevant network Quality of Service (QoS) conditions. Many of those derive from the E-model, ITU-T standard for network planning in voice transmission applications. The E-model maps the values of different network conditions into a common Transmission Rating scale, which is later used to estimate user quality scores. However, the E-model does not provide a method to obtain direct human judgments on such scale, which has also found not applicable to other applications, such as web browsing or video. In this paper, we propose a way to use the Transmission Rating for general use cases, including video quality. Be re-doing the derivation process which led to the E-model scale from the original Bellcore model, it is possible to apply it to any use case with an underlying normal distribution of subjective scores. We validate this approach by analyzing two video quality experiments which mix different judgement conditions (in particular, screen sizes and resolutions). Finally, we provide general recommendations to develop Transmission Rating scales in future parametric models.

This paper proposes a methodology to assess video quality, spatial and social presence, empathy, attitude, and attention in 360-degree videos for immersive communications. The methodology is validated in an experiment which simulates an immersive communication environment where participants attend three conversations of different genre (everyday conversation, educational, and discussion) and from actor and observer acquisition perspectives. We consider three experimental conditions: (A) visualizing and rating the perceptual quality of contents in a Head-Mounted Display (HMD), (B) visualizing the contents in an HMD, and (C) visualizing the contents in an HMD where participants can see their hands and take notes. In all conditions participants visualize the same 360-degree videos, designed and acquired in the context of international experiences. Fifty-four participants were evenly distributed among A, B, and C conditions taking into account their international experience backgrounds (working or studying in a foreign country), obtaining a balanced and diverse sample of participants. Finally, the annotated dataset, Student Experiences Around the World dataset (SEAW-dataset), obtained from the experiment is made publicly available for the research community.

Subjective responses from Multimedia Quality Assessment (MQA) experiments are conventionally analyzed with methods not suitable for the data type these responses represent. Furthermore, obtaining subjective responses is resource intensive. Thus, a method that allows the reuse of existing responses would be beneficial. Applying improper data analysis methods leads to difficulty in interpreting results. This increases the probability of drawing erroneous conclusions. Building upon existing subjective responses is resource friendly and helps develop machine learning (ML) based visual quality predictors. In this work, we show that using a discrete model for analyzing responses from MQA subjective experiments is feasible. We indicate that our proposed Generalized Score Distribution (GSD) properly describes response distributions observed in typical MQA experiments. We also highlight interpretability of GSD parameters and indicate that the GSD outperforms the approach based on sample empirical distribution when it comes to bootstrapping. Furthermore, we provide evidence that the GSD outcompetes the state-of-the-art model both in terms of goodness-of-fit and bootstrapping capabilities. To accomplish the aforementioned objectives, we analyze more than one million subjective responses from over 30 subjective experiments.

The rise of eXtended Reality (XR) has led to multiple ways of including the user’s body in interactive experiences. However, the delay limits of self-view rendering in interactive XR remain unexplored. This article presents a minimum self-view latency system and an interactive task-based experiment to study the influence of different levels of self-view delay on Quality of Experience (QoE) and task performance. During the experiment, 23 users tested 8 delay conditions (from 190 to 597 ms) while building block-based models. The results show a hard threshold in terms of involvement and overall quality around 450ms. However, the impact on adaptation and execution time was less pronounced. This indicates that although users adapted to the task in a certain way, their immersion was severely affected above a certain self-view delay value.

The preliminary results of immersive virtual reality music therapy experiences are presented, carried out with people between ages of 72 and 96, residents of a nursing home, who suffer from mild mental health problems, potential dementia, moderate cognitive disorders, depressive symptoms, or severe dependency. The experiences are carried out in 15-minute sessions, streaming 180° and 360° music videos of genres that the elderly like, recorded for this purpose and performed by musical groups that collaborate voluntarily. The design of the developed application (the web interface, the application logic and the HMD player) is simple so that it is easy to use during music therapy sessions. Preliminary results show that the elderly experience similar levels of sense of presence as reported by other studies in younger population (< 55), and only 19% of them suffer from simulator sickness. This validates the usage of immersive media for music therapy in elderly patients.

Cybersickness involves all the adverse effects that can occur during a Virtual Reality (VR) immersion, which can compromise the quality of the user experience and limit the usability, functionality and duration of use of VR systems. Standardised protocols help detect stimuli that may cause cybersickness in multiple users but do not fully discriminate which specific users experience cybersickness. Of the biometric measures used to monitor cybersickness in an individual, Heart Rate Variability (HRV) is one of the most used in previous work. However, these only considered its temporal components and did not allow for rest periods between sessions, even though these can affect users’ immersion. Our analysis addresses these limitations in that changes in HRV can measure specific levels of discomfort or ”alertness” associated with the initial cybersickness stimulus induced in the 360 videos. Primarily, our empirical results show significant differences in the frequency components of HRV in response to cybersickness stimuli. These initial measurements can compete with standard subjective assessment protocols, especially for detecting whether a subject responds to a VR immersion with cybersickness symptoms.

Task offloading has become a key term in the field of immersive media technologies: it can enable lighter and cheaper devices while providing them higher remote computational capabilities. In this paper we present our TCP-based offloading architecture. The architecture, has been specifically designed for immersive media offloading tasks with a particular care in reducing any processing overhead which can degrade the network performance. We tested the architecture for different offloading scenarios and conditions on two different wireless networks: WiFi and 5G millimeter wave technologies. Besides, to test the network on alternative millimeter wave configurations, currently not available on the actual 5G millimeter rollouts, we used a 5G Radio Access Network (RAN) real-time emulator. This emulator was also used to test the offloading architecture for an simulated immersive user sharing network resources with other users. We provide insights of the importance of user prioritization techniques for successful immersive media offloading. The results show a great performance for the tested immersive media scenarios, highlighting the relevance of millimeter wave technology for the future of immersive media applications.

Tele-education was already a solution for people who cannot attend lessons in person (such as inaccessibility in rural areas or illness issues). However, COVID has revealed problems in tele-education with current technology, causing adolescents and children to slow down their learning curves and experience problems of social distancing with their classmates. This paper presents a user study to validate an immersive communication system for tele-education purposes. This system streams in real time a class using 360-degree cameras, allowing remote students to explore the whole scene and improving the feeling of being in the classroom with their colleagues. Additionally, the prototype provides notifications to the remote students about events (such as a changes in the teacher’s presentation or classmates raising their hands) that occur outside their viewport to indicate in which direction they should move their heads to visualize them.

Recently an impressive development in immersive technologies, such as Augmented Reality (AR), Virtual Reality (VR) and 360${^\circ }$video, has been witnessed. However, methods for quality assessment have not been keeping up. This paper studies quality assessment of 360${^\circ }$video from the cross-lab tests (involving ten laboratories and more than 300 participants) carried out by the Immersive Media Group (IMG) of the Video Quality Experts Group (VQEG). These tests were addressed to assess and validate subjective evaluation methodologies for 360${^\circ }$video. Audiovisual quality, simulator sickness symptoms, and exploration behavior were evaluated with short (from 10 seconds to 30 seconds) 360${^\circ }$sequences. The following factors’ influences were also analyzed: assessment methodology, sequence duration, Head-Mounted Display (HMD) device, uniform and non-uniform coding degradations, and simulator sickness assessment methods. The obtained results have demonstrated the validity of Absolute Category Rating (ACR) and Degradation Category Rating (DCR) for subjective tests with 360${^\circ }$videos, the possibility of using 10-second videos (with or without audio) when addressing quality evaluation of coding artifacts, as well as any commercial HMD (satisfying minimum requirements). Also, more efficient methods than the long Simulator Sickness Questionnaire (SSQ) have been proposed to evaluate related symptoms with 360${^\circ }$videos. These results have been instrumental for the development of the ITU-T Recommendation P.919. Finally, the annotated dataset from the tests is made publicly available for the research community.

Recent studies have shown that it is possible to characterize subject bias and variance in subjective assessment tests. Apparent differences among subjects can, for the most part, be explained by random factors. Building on that theory, we propose a subjective test design where four to six team members each rate the stimuli multiple times. The results are comparable to a high performing objective metric. This provides a quick and simple way to analyze new technologies and perform pre-tests for subjective assessment.

This work-in-progress presents a dataset of 360degree videos, called EVENT-CLASS, with associated characteristics in the context of tele-education. The sequences (video and audio) have been captured considering several environments, lighting conditions, acquisition perspectives, and cameras, enriching the dataset. EVENT-CLASS will be helpful for numerous applications related to tele-education, including quality assessment tests, and with the aim of improving the immersive experience of remote users thanks to the detection of relevant events that happen in the class. In this sense, this paper presents preliminary results of using transfer learning for person detection in 360degree scenes, based on Detectron2, and provides insights on the influence of applying it to equirectangular projection and over the viewport. Ongoing works will allow to include more videos and ground-truth annotations to the dataset.

Current extended reality applications use omnidirectional video to boost users' immersion and sense of presence. As contents from distant video sources cannot be instantaneously delivered, the end-to-end delay becomes a key problem when user actions cannot be simultaneously matched by system reactions. Thus, we have designed and executed an experiment to assess its influence on the quality of experience, the sense of presence, and the sickness caused. To do it, we have developed a viewport adaptive simulator to render simultaneously two layers of immersive video to allow different adaptation schemes and delay values. Twenty observers have assessed 180 test videos from 9 sources. Our analysis shows a clear influence of the delay condition and the adaptation scheme on the perceived quality. Moreover, it also shows that the adaptation schemes and delay conditions have a small influence on the sense of presence and little effect on observers sickness.

A novel Key Quality Indicator for video delivery applications, XLR (piXel Loss Rate), is defined, characterized, and evaluated. The proposed indicator is an objective measure that captures the effects of transmission errors in the received video, has a good correlation with subjective Mean Opinion Scores, and provides comparable results with state-of-the-art Full-Reference metrics. Moreover, XLR can be estimated using only a lightweight analysis on the compressed bitstream, thus allowing a No-Reference operational method. Therefore, XLR can be used for measuring the quality of experience without latency at any network location. Thus, it is a relevant tool for network planning, specially in new high-demanding scenarios. The experiments carried out show the outstanding performance of its linear-dimension score and the reliability of the bitstream-based estimation.

This paper describes MIRO360, a tool which implements the diverse set of methodologies that are being evaluated by ITU-T Study Group 12 and the Video Quality Experts Group in the development of the future ITU-T Recommendation P.360-VR for the subjective assessment of 360 video with Head Mounted Displays (HMDs). MIRO360 is an application for Android-based HMDs, with a flexible configuration that allows the simple creation of tests for short sequences (either single or double reference), as well as for long ones, including in-sequence continuous or discrete evaluation, as well as simulator sickness and spatial presence.

Adaptive Media Playout (AMP), the adaptive modification of media playback speed, has been previously proposed as a technique to modify the playout delay of a user with respect to other users or with real time, thus having a crucial role in social TV and live video streaming. In this paper, we study the subjective impact of the playout rate change, which had received very limited attention in the past. In particular, we analyze the effect of the subject and the source content in the subjective opinion.We have found that most of the previous works underestimated the impact of AMP in perceived quality, and that the speed change rate should not be modified beyond 10% from the original, as a general rule. We have also developed a user scoring model which takes into account the variability between users and sources. Our results can help developing cost models for playout control systems based on AMP, as well as provide some insights to the analysis of other types of subjective assessment tests.

Simulator sickness and visual discomfort are known undesired effects of immersive media systems. In this paper, we propose a methodology to systematically evaluate the effect of camera motion in cybersickness for omnidirectional video contents. By simulating camera motion, we have isolated its effect from other content factors, showing that sickness depends on the motion pattern amplitude and frequency. We have also found that discomfort can be mitigated by introducing fixed-position visual anchors. This could help in the prevention of cybersickness on sensitive users.

Although the delivery of 3D video services to households is nowadays a reality thanks to frame-compatible formats, many efforts are being made to obtain efficient methods to transmit 3D content offering a high quality of experience to the end users. In this paper, a stereoscopic video streaming scenario is considered, and the perceptual impact of various strategies applicable to adaptive streaming situations are compared. Specifically, the mechanisms are based on switching between copies of the content with different coding qualities, on discarding frames of the sequence, on switching from 3D to 2D, and on using asymmetric coding of the stereo views. In addition, when video freezes happen, the possibility of keeping the end-to-end latency or maintaining the continuity of the video are considered. These aspects were evaluated carrying out a subjective assessment test, considering also visual discomfort issues, using a methodology designed to keep as far as possible domestic viewing conditions.

Real-time monitoring of multimedia Quality of Experience is a critical task for the providers of multimedia delivery services: from television broadcasters to IP content delivery networks or IPTV. For such scenarios, meaningful metrics are required which can generate useful information to the service providers that overcome the limitations of pure Quality of Service monitoring probes. However, most of objective multimedia quality estimators, aimed at modeling the Mean Opinion Score, are difficult to apply to massive quality monitoring. Thus we propose a lightweight and scalable monitoring architecture called Qualitative Experience Monitoring (QuEM), based on detecting identifiable impairment events such as the ones reported by the customers of those services. We also carried out a subjective assessment test to validate the approach and calibrate the metrics. Preliminary results of this test set support our approach.

The increase of multimedia services delivered over packet-based networks has entailed greater quality expectations of the end-users. This has led to an intensive research on techniques for evaluating the quality of experience perceived by the viewers of audiovisual content, considering the different degradations that it could suffer along the broadcasting system. In this paper, a comprehensive study of the impact of transmission errors affecting video and audio in IPTV is presented. With this aim, subjective assessment tests were carried out proposing a novel methodology trying to keep as close as possible home environment viewing conditions. Also 3DTV content in side-by-side format has been used in the experiments to compare the impact of the degradations. The results provide a better understanding of the effects of transmission errors, and show that the QoE related to the first approach of 3DTV is acceptable, but the visual discomfort that it causes should be reduced.

Nowadays, low-cost digital cameras embedded in mobile phones are becoming the main source of visual information. Nevertheless, its use is restricted to simple store and forward applications due to the limitations in the spatial resolution and dynamic range of those cameras. A registration algorithm is proposed to allow image mosaicing and therefore to increase camera applications. It is able to find the geometric relation between any image in the set, lacking any prior knowledge of the relative position and exposure of any image in the set, and working on low-overlapping pairs. It also deals with partial occlusions. The registration algorithm is based on the use of Zernike moments and RANSAC robust fitting to guarantee stability, and KLT tracker to provide accuracy. Besides, a radiometric compensation stage allows the development of a completely automatic and seamless mosaicing system.