Real-Time Estimation of Illumination Direction for Augmented Reality with Low-Cost Sensors

In recent years, Augmented Reality has become a very popular topic, both as a research and commercial field. This trend has originated with the use of mobile devices as computational core and display. The appearance of virtual objects and their interaction with the real world is a key element in the success of an Augmented Reality software. A common issue in this type of software is the visual inconsistency between the virtual and real objects due to wrong illumination. Although illumination is a common research topic in Computer Graphics, few studies have been made about real time estimation of illumination direction. In this work we present a low-cost approach to detect the direction of the environment illumination, allowing the illumination of virtual objects according to the real light of the ambient, improving the integration of the scene. Our solution is open-source, based on Arduino hardware and the presented system was developed on Android.XIV Workshop Computación Gráfica, Imágenes y Visualización (WCGIV).Red de Universidades con Carreras en Informática (RedUNCI

Real-Time Estimation of Illumination Direction for Augmented Reality with Low-Cost Sensors

In recent years, Augmented Reality has become a very popular topic, both as a research and commercial field. This trend has originated with the use of mobile devices as computational core and display. The appearance of virtual objects and their interaction with the real world is a key element in the success of an Augmented Reality software. A common issue in this type of software is the visual inconsistency between the virtual and real objects due to wrong illumination. Although illumination is a common research topic in Computer Graphics, few studies have been made about real time estimation of illumination direction. In this work we present a low-cost approach to detect the direction of the environment illumination, allowing the illumination of virtual objects according to the real light of the ambient, improving the integration of the scene. Our solution is open-source, based on Arduino hardware and the presented system was developed on Android.XIV Workshop Computación Gráfica, Imágenes y Visualización (WCGIV).Red de Universidades con Carreras en Informática (RedUNCI

Generating Light Estimation for Mixed-reality Devices through Collaborative Visual Sensing

abstract: Mixed reality mobile platforms co-locate virtual objects with physical spaces, creating immersive user experiences. To create visual harmony between virtual and physical spaces, the virtual scene must be accurately illuminated with realistic physical lighting. To this end, a system was designed that Generates Light Estimation Across Mixed-reality (GLEAM) devices to continually sense realistic lighting of a physical scene in all directions. GLEAM optionally operate across multiple mobile mixed-reality devices to leverage collaborative multi-viewpoint sensing for improved estimation. The system implements policies that prioritize resolution, coverage, or update interval of the illumination estimation depending on the situational needs of the virtual scene and physical environment. To evaluate the runtime performance and perceptual efficacy of the system, GLEAM was implemented on the Unity 3D Game Engine. The implementation was deployed on Android and iOS devices. On these implementations, GLEAM can prioritize dynamic estimation with update intervals as low as 15 ms or prioritize high spatial quality with update intervals of 200 ms. User studies across 99 participants and 26 scene comparisons reported a preference towards GLEAM over other lighting techniques in 66.67% of the presented augmented scenes and indifference in 12.57% of the scenes. A controlled lighting user study on 18 participants revealed a general preference for policies that strike a balance between resolution and update rate.Dissertation/ThesisMasters Thesis Computer Science 201

Static scene illumination estimation from video with applications

We present a system that automatically recovers scene geometry and illumination from a video, providing a basis for various applications. Previous image based illumination estimation methods require either user interaction or external information in the form of a database. We adopt structure-from-motion and multi-view stereo for initial scene reconstruction, and then estimate an environment map represented by spherical harmonics (as these perform better than other bases). We also demonstrate several video editing applications that exploit the recovered geometry and illumination, including object insertion (e.g., for augmented reality), shadow detection, and video relighting

Self-supervised Outdoor Scene Relighting

Outdoor scene relighting is a challenging problem that requires good understanding of the scene geometry, illumination and albedo. Current techniques are completely supervised, requiring high quality synthetic renderings to train a solution. Such renderings are synthesized using priors learned from limited data. In contrast, we propose a self-supervised approach for relighting. Our approach is trained only on corpora of images collected from the internet without any user-supervision. This virtually endless source of training data allows training a general relighting solution. Our approach first decomposes an image into its albedo, geometry and illumination. A novel relighting is then produced by modifying the illumination parameters. Our solution capture shadow using a dedicated shadow prediction map, and does not rely on accurate geometry estimation. We evaluate our technique subjectively and objectively using a new dataset with ground-truth relighting. Results show the ability of our technique to produce photo-realistic and physically plausible results, that generalizes to unseen scenes.Comment: Published in ECCV '20, http://gvv.mpi-inf.mpg.de/projects/SelfRelight

Estimating Illumination Direction for Augmented Reality in Real-Time by using Low-Cost Sensors

In recent years, Augmented Reality has become a very popular topic, both as a research and commercial field. This trend has originated with the use of mobile devices as computational core and display. The appearance of virtual objects and their interaction with the real world is a key element in the success of an Augmented Reality software. A common issue in this type of software is the visual inconsistency between the virtual and real objects due to wrong illumination. Although illumination is a common research topic in Computer Graphics, few studies have been made about real time estimation of illumination direction. In this work we present a low-cost approach to detect the direction of the environment illumination, allowing the illumination of virtual objects according to the real light of the ambient, improving the integration of the scene. Our solution is open-source, based on Arduino hardware and the presented system was developed on Android.Facultad de Informátic

Real-Time Estimation of Illumination Direction for Augmented Reality with Low-Cost Sensors

In recent years, Augmented Reality has become a very popular topic, both as a research and commercial field. This trend has originated with the use of mobile devices as computational core and display. The appearance of virtual objects and their interaction with the real world is a key element in the success of an Augmented Reality software. A common issue in this type of software is the visual inconsistency between the virtual and real objects due to wrong illumination. Although illumination is a common research topic in Computer Graphics, few studies have been made about real time estimation of illumination direction. In this work we present a low-cost approach to detect the direction of the environment illumination, allowing the illumination of virtual objects according to the real light of the ambient, improving the integration of the scene. Our solution is open-source, based on Arduino hardware and the presented system was developed on Android.XIV Workshop Computación Gráfica, Imágenes y Visualización (WCGIV).Red de Universidades con Carreras en Informática (RedUNCI