Designing a mixed reality interface for autonomous robot-based change detection

2021 ◽  
Author(s):  
Christopher Reardon ◽  
Jason M. Gregory ◽  
Carlos P. Nieto-Granda ◽  
John G. Rogers
Keyword(s):  
Change Detection ◽  
Mixed Reality ◽  
Autonomous Robot

Mixed reality environment for autonomous robot development

2008 ◽  
Author(s):  
Koichi Nishiwaki ◽  
Kazuhiko Kobayashi ◽  
Shinji Uchiyama ◽  
Hiroyuki Yamamoto ◽  
Satoshi Kagami
Keyword(s):  
Mixed Reality ◽  
Autonomous Robot

scholarly journals Detection of Removed Objects in 3D Meshes Using Up-to-Date Images for Mixed-Reality Applications

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 377
Author(s):  
Olivier Roupin ◽  
Matthieu Fradet ◽  
Caroline Baillard ◽  
Guillaume Moreau
Keyword(s):  
Change Detection ◽  
Virtual Worlds ◽  
Mixed Reality ◽  
Detection Algorithm ◽  
The Real ◽  
Real Environment ◽  
Hybrid Approaches ◽  
Precise Knowledge ◽  
Change Detection Algorithms ◽  
Live Image

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.

Effects of Using Mixed Reality With Coaching on the Interprofessional Communication Skills of Speech-Language Pathology Graduate Students

2021 ◽  
pp. 1-21
Author(s):  
Jacqueline A. Towson ◽  
Matthew S. Taylor ◽  
Diana L. Abarca ◽  
Claire Donehower Paul ◽  
Faith Ezekiel-Wilder
Keyword(s):  
Graduate Students ◽  
Self Efficacy ◽  
Mixed Reality ◽  
Role Play ◽  
Speech Language Pathology ◽  
Traditional Role ◽  
Allied Health Professionals ◽  
Interprofessional Communication ◽  
Language Pathology ◽  
The Individual

Purpose Communication between allied health professionals, teachers, and family members is a critical skill when addressing and providing for the individual needs of patients. Graduate students in speech-language pathology programs often have limited opportunities to practice these skills prior to or during externship placements. The purpose of this study was to research a mixed reality simulator as a viable option for speech-language pathology graduate students to practice interprofessional communication (IPC) skills delivering diagnostic information to different stakeholders compared to traditional role-play scenarios. Method Eighty graduate students ( N = 80) completing their third semester in one speech-language pathology program were randomly assigned to one of four conditions: mixed-reality simulation with and without coaching or role play with and without coaching. Data were collected on students' self-efficacy, IPC skills pre- and postintervention, and perceptions of the intervention. Results The students in the two coaching groups scored significantly higher than the students in the noncoaching groups on observed IPC skills. There were no significant differences in students' self-efficacy. Students' responses on social validity measures showed both interventions, including coaching, were acceptable and feasible. Conclusions Findings indicated that coaching paired with either mixed-reality simulation or role play are viable methods to target improvement of IPC skills for graduate students in speech-language pathology. These findings are particularly relevant given the recent approval for students to obtain clinical hours in simulated environments.

Vivid Imagers Are Better at Detecting Salient Changes

2006 ◽  
Vol 27 (4) ◽  
pp. 218-228 ◽  
Author(s):  
Paul Rodway ◽  
Karen Gillies ◽  
Astrid Schepman
Keyword(s):  
Individual Differences ◽  
Change Detection ◽  
Visual Imagery ◽  
Detection Task ◽  
Level Of Detail ◽  
Detection Accuracy ◽  
Change Detection Task ◽  
Term Change ◽  
High Level

This study examined whether individual differences in the vividness of visual imagery influenced performance on a novel long-term change detection task. Participants were presented with a sequence of pictures, with each picture and its title displayed for 17  s, and then presented with changed or unchanged versions of those pictures and asked to detect whether the picture had been changed. Cuing the retrieval of the picture's image, by presenting the picture's title before the arrival of the changed picture, facilitated change detection accuracy. This suggests that the retrieval of the picture's representation immunizes it against overwriting by the arrival of the changed picture. The high and low vividness participants did not differ in overall levels of change detection accuracy. However, in replication of Gur and Hilgard (1975) , high vividness participants were significantly more accurate at detecting salient changes to pictures compared to low vividness participants. The results suggest that vivid images are not characterised by a high level of detail and that vivid imagery enhances memory for the salient aspects of a scene but not all of the details of a scene. Possible causes of this difference, and how they may lead to an understanding of individual differences in change detection, are considered.

An attentional bias for LEGO® people using a change detection task: Are LEGO® people animate?

2016 ◽  
Vol 70 (3) ◽  
pp. 219-231 ◽  
Author(s):  
Mitchell R. P. LaPointe ◽  
Rachael Cullen ◽  
Bianca Baltaretu ◽  
Melissa Campos ◽  
Natalie Michalski ◽  
...  
Keyword(s):  
Change Detection ◽  
Attentional Bias ◽  
Detection Task ◽  
Change Detection Task
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