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Watching a 360◦ sports video requires a viewer to continuously select a viewing angle, either through a sequence of mouse clicks or head movements. To relieve the viewer from this “360 piloting” task, we propose “deep 360 pilot” – a deep learning-based agent for piloting through 360◦ sports videos automatically. At each frame, the agent observes a panoramic(More)
360° videos give viewers a spherical view and immersive experience of surroundings. However, one challenge of watching 360° videos is continuously focusing and re-focusing intended targets. To address this challenge, we developed two Focus Assistance techniques: Auto Pilot (directly bringing viewers to the target), and Visual Guidance (indicating(More)
Watching a 360 sports video requires a viewer to continuously select a viewing angle, either through a sequence of mouse clicks or head movements. To relieve the viewer from this “360 piloting” task, we propose “deep 360 pilot” – a deep learning-based agent for piloting through 360 sports videos automatically. At each frame, the agent observes a panoramic(More)
r(lt(i), l gt t ) = { 1− ‖lt(i)−l gt t ‖2 η , if ‖lt(i)− l gt t ‖2 <= η −1, otherwise (1) where η equals the distance from the center of a viewing angle to the corner of its corresponding NFoV, i.e., √ 32.752 + 24.562 = 40.9 if we define NFOV as spanning a horizontal angle of 65.5◦ with a 4 : 3 aspect ratio. When lt == l gt t , the reward is 1, which is the(More)
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