SmartVP: Viewpoint Optimization Based on Individual Preference for Watching 3D Boxing Punch Videos

When broadcasting the 3D boxing punch videos, spectators may have different preferences for spectating. Some people prefer to see the hitting point, while others want to see the punching form. It is not easy to provide a uniformly optimal viewpoint. In this paper, we introduce a novel method to select an optimal viewpoint for watching punching moments in VR that can handle different spectator preferences. We customize a visibility model that utilizes 8 bounding boxes to account for the visibility of upper body parts. We use a neural network classification model to reproduce the optimal viewpoint selection based on the features of body parts visibility, punch side, and punch offset. We collected spectators’ preferred viewpoints from 24 participants under 3 controlled preference conditions: seeing the punch Arm Form clearly (AF), seeing the Facial Expression clearly (FE), and no additional restriction (None). We conducted a user study to evaluate the empirical performance of our system. The training and user study results show that our method can reproduce the optimal viewpoint with spectator preference.