Markerless motion capture and understanding of professional non-daily human movements is an important yet unsolved task, which suffers from complex motion patterns and severe self-occlusion, especially for the monocular setting. In this paper, we propose SportsCap -- the first approach for simultaneously capturing 3D human motions and understanding fine-grained actions from monocular challenging sports video input.
About SportCaps :
SportsCap proposes a challenging sports dataset called Sports Motion and Recognition Tasks (SMART) dataset, which contains per-frame action labels, manually annotated pose, and action assessment of various challenging sports video clips from professional referees.
Their approaches :
This is especially prevalent in non-daily action classes like fitness and sports domains. This can be mitigated, for example, by annotating domain-specific datasets , but that requires a considerable amount of manual annotation efforts, financial resources, and 3D annotations can only be obtained in controlled conditions. Therefore, we propose to learn domain-specific pose-sensitive representations from unlabeled videos, which can be fine tuned using only a small labeled dataset. ...
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They spread the catholic faith throughout the new world
Answer:
"Facial-feedback hypothesis"
Explanation:
In psychology, the idea behind the facial-feedback hypothesis is that the facial expressions we make directly influence our emotional experiences.
The question mentions that Kathyrn seemed to enjoy the show more once she was prompted by her mom to smile while watching it. This would be a prime example of this theory. I hope this helped!
