2016
DOI: 10.1007/s41095-016-0053-5
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Synthesis of a stroboscopic image from a hand-held camera sequence for a sports analysis

Abstract: This paper presents a method for synthesizing a stroboscopic image of a moving sports player from a hand-held camera sequence. This method has three steps: synthesis of background image, synthesis of stroboscopic image, and removal of player's shadow. In synthesis of background image step, all input frames masked a bounding box of the player are stitched together to generate a background image. The player is extracted by an HOG-based people detector. In synthesis of stroboscopic image step, the background imag… Show more

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Cited by 9 publications
(3 citation statements)
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References 28 publications
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“…For performance analysis of individual athletes, [10] propose a method to facilitate speed and stride length estimation for runners based on hand-held camera recordings. Specific to an aquatic environment, [22] describe how swimmers can be tracked when filmed by a moving camera above the water surface.…”
Section: Related Workmentioning
confidence: 99%
“…For performance analysis of individual athletes, [10] propose a method to facilitate speed and stride length estimation for runners based on hand-held camera recordings. Specific to an aquatic environment, [22] describe how swimmers can be tracked when filmed by a moving camera above the water surface.…”
Section: Related Workmentioning
confidence: 99%
“…Tanahashi et al [59] proposed an efficient framework for storyline visualization from streaming video data. Hasegawa and Saito [60] presents a method for synthesis stroboscopic image from video sequence for sports analysis.…”
Section: Visual Content Synthesismentioning
confidence: 99%
“…The multi-camera systems [17] - [21] are also designed to track human, but those approaches only process in a small area which installs cameras. The hand-held cameras system is equipped for the sports player in [22] to synthesize a stroboscopic image of a moving target. Nevertheless, its computational speed and accuracy could not be optimal in case of the elaborate environments.…”
Section: Introductionmentioning
confidence: 99%