Visual Tracking Method of a Quick and Anomalously Moving Badminton Shuttlecock

This paper introduces a method that uses multiple-view videos to estimate the 3D position of a badminton shuttle that moves quickly and anomalously. When an object moves quickly, it is observed with a motion blur effect. By utilizing the information provided by the shape of the motion blur region, we propose a visual tracking method for objects that have an erratic and drastically changing moving speed. When the speed increases tremendously, we propose another method, which applies the shape-from-silhouette technique, to estimate the 3D position of a moving shuttlecock using unsynchronized multiple-view videos. We confirmed the effectiveness of our proposed technique using video sequences and a CG simulation image set

Constrained multi-target tracking for team sports activities

Abstract In sports analysis, player tracking is essential to the extraction of statistics such as speed, distance and direction of motion. Simultaneous tracking of multiple people is still a very challenging computer vision problem to which there is no satisfactory solution. This is especially true for sports activities, for which people often wear similar uniforms, move quickly and erratically, and have close interactions with each other. In this paper, we introduce a multi-target tracking algorithm suitable for team sports activities. We extend an existing algorithm by including an automatic estimation of the occupancy of the observed field and the duration of stable periods without people entering or leaving the field. This information is included as a constraint to the existing offline tracking algorithm in order to construct more reliable trajectories. On data from two challenging sports scenarios—an indoor soccer game captured with thermal cameras and an outdoor soccer training session captured with RGB camera—we show that the tracking performance is improved on all sequences. Compared to the original offline tracking algorithm, we obtain improvements of 3–7% in accuracy. Furthermore, the method outperforms two state-of-the-art trackers

Improving Global Multi-target Tracking with Local Updates

Conference dates: September 6-7 & 12, 2014We propose a scheme to explicitly detect and resolve ambiguous situations in multiple target tracking. During periods of uncertainty, our method applies multiple local single target trackers to hypothesise short term tracks. These tracks are combined with the tracks obtained by a global multi-target tracker, if they result in a reduction in the global cost function. Since tracking failures typically arise when targets become occluded, we propose a local data association scheme to maintain the target identities in these situations. We demonstrate a reduction of up to 50% in the global cost function, which in turn leads to superior performance on several challenging benchmark sequences. Additionally, we show tracking results in sports videos where poor video quality and frequent and severe occlusions between multiple players pose difficulties for state-of-the-art trackers.Anton Milan, Rikke Gade, Anthony Dick, Thomas B. Moeslund, and Ian Rei

Improvement of Badminton-Player Tracking Applying Image Pixel Compensation

Motion analysis of athletes often provides important information to improve training and strategy meetings. Visual player-tracking techniques are being developed that do not need devices. In this paper, we focus on racket sports, since they suffer from technical issues for visual tracking such as small observation size (low resolution) and large variation of player appearances. Moreover, racket sports video is usually captured by a monocular camera at a set position so that each player is observed at a top and a bottom region of the video across a net on the court. As a result, tracking accuracy is damaged by the net that often occludes players on the far side. As a solution, this paper proposes a method to improve the player-tracking accuracy in badminton video by applying an image pixel compensation technique, such as Image Inpainting. We confirm the effectiveness of our method using videos of badminton singles games