Synthesis of a stroboscopic image from a hand-held camera sequence for a sports analysis

Kunihiro Hasegawa, Hideo Saito

Research output: Contribution to journalArticle

6 Citations (Scopus)

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 image, the input frame, and a mask of the player synthesize a stroboscopic image. In removal of shadow step, we remove the player’s shadow which negatively affects an analysis by using mean-shift. In our previous work, synthesis of background image has been timeconsuming. In this paper, by using the bounding box of the player detected by HOG and by subtracting the images for synthesizing a mask, computational speed and accuracy can be improved. These have contributed greatly to the improvement from the previous method. These are main improvements and novelty points from our previous method. In experiments, we confirmed the effectiveness of the proposed method, measured the player’s speed and stride length, and made a footprint image. The image sequence was captured under a simple condition that no other people were in the background and the person controlling the video camera was standing still, such like a motion parallax was not occurred. In addition, we applied the synthesis method to various scenes to confirm its versatility.

Original languageEnglish
Pages (from-to)277-289
Number of pages13
JournalComputational Visual Media
Volume2
Issue number3
DOIs
Publication statusPublished - 2016 Sep 1

Keywords

  • mask
  • sports vision
  • stitching
  • stroboscopic image
  • synthesis

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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