1. Detection of Removed Objects in 3D Meshes Using Up-to-Date Images for Mixed-Reality Applications
- Author
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Caroline Baillard, Guillaume Moreau, Olivier Roupin, Matthieu Fradet, InterDigital R&D France, Département Informatique (IMT Atlantique - INFO), IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Equipe Immersive Natural User Interaction team (Lab-STICC_INUIT), Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), and Institut Mines-Télécom [Paris] (IMT)
- Subjects
3D model ,Computer Networks and Communications ,Computer science ,lcsh:TK7800-8360 ,projection ,02 engineering and technology ,foreground object ,0202 electrical engineering, electronic engineering, information engineering ,Polygon mesh ,Computer vision ,Electrical and Electronic Engineering ,Projection (set theory) ,change detection ,mixed reality ,business.industry ,lcsh:Electronics ,Process (computing) ,020207 software engineering ,Object (computer science) ,Mixed reality ,[INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR] ,image sequence ,Hardware and Architecture ,Control and Systems Engineering ,Signal Processing ,020201 artificial intelligence & image processing ,Artificial intelligence ,occluding object ,business ,Change detection - Abstract
Precise knowledge of the real environment is a prerequisite for the integration of the real and virtual worlds in mixed-reality applications. However, real-time updating of a real environment model is a costly and difficult process, therefore, hybrid approaches have been developed: An updated world model can be inferred from an offline acquisition of the 3D world, which is then updated online using live image sequences under the condition of developing fast and robust change detection algorithms. Current algorithms are biased toward object insertion and often fail in object removal detection, in an environment where there is uniformity in the background—in color and intensity—the disappearances of foreground objects between the 3D scan of a scene and the capture of several new pictures of said scene are difficult to detect. The novelty of our approach is that we circumvent this issue by focusing on areas of least change in parts of the scene that should be occluded by the foreground. Through experimentation on realistic datasets, we show that this approach results in better detection and localization of removed objects. This technique can be paired with an insertion detection algorithm to provide a complete change detection framework.
- Published
- 2021
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