Abstract | ||
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Computer vision enables camera data to be utilized in user interfaces to analyze the 3-D context and automatically detect the user intentions. Using cameras as an input modality provides single-handed operations in which the users' actions are recognized without interactions with the screen or keypad. In this context, we have constructed a real-time mobile application prototype where the user's position and gaze is determined in real time, a technique that enables the display of true three-dimensional objects even on a typical 2-D LCD screen. We have defined a series of interaction methods where the user's motion and camera input realistically control the viewpoint on a 3-D scene. The head movement and gaze can be used to interact with hidden objects in a natural manner just by looking at them. We provide a description of the embedded implementation at a system-level where we highlight the application development challenges and trade-offs that need to be dealt with battery powered mobile devices. The implementation includes a parallel pipeline that reduces the latencies of the application. |
Year | DOI | Venue |
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2012 | 10.1109/CVPRW.2012.6238891 | CVPR Workshops |
Keywords | Field | DocType |
computer vision,mobile computing,object recognition,object tracking,parallel processing,pipeline processing,screens (display),user interfaces,virtual reality,2D LCD screen,3D context analysis,battery powered mobile devices,camera input,computer vision,gaze,head movement,head-tracking virtual 3D display,interaction methods,parallel pipeline,real-time mobile application prototype,three-dimensional objects,user action recognition,user intention detection,user interfaces,user motion | Mobile computing,Keypad,Computer vision,Virtual reality,Gaze,Computer science,Mobile device,Video tracking,Artificial intelligence,User interface,Mobile telephony | Conference |
Volume | Issue | ISSN |
2012 | 1 | 2160-7508 |
Citations | PageRank | References |
6 | 0.47 | 17 |
Authors | ||
4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Miguel Bordallo López | 1 | 67 | 7.54 |
Jari Hannuksela | 2 | 121 | 13.36 |
Olli Silvén | 3 | 303 | 38.76 |
Lixin Fan | 4 | 131 | 20.15 |