Panoramic Video Construction from Mobile Video Streams

2015 ◽  
pp. 61-83
Author(s):  
Motaz El Saban ◽  
Ayman Kaheel
Keyword(s):  
Mobile Video ◽  
Video Streams ◽  
Panoramic Video

Frustration and Violence in Mobile Video Games

2020 ◽  
Vol 79 (2) ◽  
pp. 63-70
Author(s):  
Petr Květon ◽  
Martin Jelínek
Keyword(s):  
Video Games ◽  
Video Game ◽  
Implicit Association Test ◽  
Self Determination Theory ◽  
Psychological Needs ◽  
Basic Psychological Needs ◽  
Self Determination ◽  
Mobile Video ◽  
Violent Content ◽  
Before And After

Abstract. This study tests two competing hypotheses, one based on the general aggression model (GAM), the other on the self-determination theory (SDT). GAM suggests that the crucial factor in video games leading to increased aggressiveness is their violent content; SDT contends that gaming is associated with aggression because of the frustration of basic psychological needs. We used a 2×2 between-subject experimental design with a sample of 128 undergraduates. We assigned each participant randomly to one experimental condition defined by a particular video game, using four mobile video games differing in the degree of violence and in the level of their frustration-invoking gameplay. Aggressiveness was measured using the implicit association test (IAT), administered before and after the playing of a video game. We found no evidence of an association between implicit aggressiveness and violent content or frustrating gameplay.

Immersive HMD 360 degree panoramic video environments for exposure therapy and anger management

2002 ◽  
Author(s):  
Albert Rizzo ◽  
Ulrich Neumann ◽  
Thomas Pintaric ◽  
Jarrell Pair
Keyword(s):  
Anger Management ◽  
Exposure Therapy ◽  
Panoramic Video

Optimal Pricing for Mobile Video Streaming in 3G Wireless Packet Networks

2012 ◽  
Vol 2 (2) ◽  
pp. 134-136
Author(s):  
Ch. Divya Ch. Divya ◽  
◽  
Dr. P. Govardhan Dr. P. Govardhan
Keyword(s):  
Video Streaming ◽  
Optimal Pricing ◽  
Packet Networks ◽  
Mobile Video ◽  
Mobile Video Streaming ◽  
Wireless Packet

Real Time Panoramic Video in OpenCV using Image Stitching Techniques

2018 ◽  
Vol 06 (03) ◽  
pp. 184-187
Author(s):  
K. Rajasri ◽  
D. Gayathri ◽  
Balasundari Ilanthirayan ◽  
A. Sundra
Keyword(s):  
Real Time ◽  
Image Stitching ◽  
Panoramic Video ◽  
Stitching Techniques

Exploring Humanistic Layers of Urban Travel

Transfers ◽  
2019 ◽  
Vol 9 (3) ◽  
pp. 99-108
Author(s):  
Jooyoung Kim ◽  
Taehee Kim ◽  
Jinhyoung Lee ◽  
Inseop Shin
Keyword(s):  
South Korea ◽  
Literary Imagination ◽  
Mobile Video ◽  
Urban Travel ◽  
Han River ◽  
Mobile Community ◽  
Restricted Region ◽  
Per Se ◽  
Relationship Of

This think piece approaches urban travel from a mobility humanities perspective, using the example of Seoul, South Korea, a leading metropolis in Asia. The article demonstrates three modes of interpreting urban travel in Seoul: (1) representation by means of mobile video technologies embodying a paradoxical relationship of powers; (2) literary imagination confining a possible mobile community in a restricted region; and (3) philosophical speculation presenting “crossing the Han River” as a spiritual and emotional reproduction of the connection between, and consequential rupture of, heterogeneous territories. The article pays particular attention to the represented, imagined, and speculated dimensions of urban travel, which is understood as a physically practiced and cognitively elaborated production, rather than a predefined movement per se.

scholarly journals Augmented Reality Maintenance Assistant Using YOLOv5

2021 ◽  
Vol 11 (11) ◽  
pp. 4758
Author(s):  
Ana Malta ◽  
Mateus Mendes ◽  
Torres Farinha
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Object Recognition ◽  
Augmented Reality ◽  
Real Time ◽  
Recognition System ◽  
High Accuracy ◽  
Video Streams ◽  
The Neural Network ◽  
Deep Learning Neural Network

Maintenance professionals and other technical staff regularly need to learn to identify new parts in car engines and other equipment. The present work proposes a model of a task assistant based on a deep learning neural network. A YOLOv5 network is used for recognizing some of the constituent parts of an automobile. A dataset of car engine images was created and eight car parts were marked in the images. Then, the neural network was trained to detect each part. The results show that YOLOv5s is able to successfully detect the parts in real time video streams, with high accuracy, thus being useful as an aid to train professionals learning to deal with new equipment using augmented reality. The architecture of an object recognition system using augmented reality glasses is also designed.

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