Multiple players tracking and identification using group detection and player number recognition in sports video

Yamamoto, Taiki; Kataoka, Hirokatsu; Aoki, Yoshimitsu; Oshima, Kyoko; Tanabiki, Masamoto

doi:10.1109/iecon.2013.6699514

Cited by 13 publications

(4 citation statements)

References 6 publications

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“…Game Analytics One of the main problems in game analytics is tracking and identification of players in videos [28,47,52]. MOTs are the first key components of the pipeline, which provide candidate detections of the players.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Optimizing Long-Term Robot Tracking with Multi-Platform Sensor Fusion

Albanese,

Mitra,

Zaech

et al. 2024

2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)

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Monitoring a fleet of robots requires stable long-term tracking with re-identification, which is yet an unsolved challenge in many scenarios. One application of this is the analysis of autonomous robotic soccer games at RoboCup. Tracking in these games requires handling of identically looking players, strong occlusions, and non-professional video recordings, but also offers state information estimated by the robots. In order to make effective use of the information coming from the robot sensors, we propose a robust tracking and identification pipeline. It fuses external noncalibrated camera data with the robots' internal states using quadratic optimization for tracklet matching. The approach is validated using game recordings from previous RoboCup World Cup tournaments.

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Section: Related Workmentioning

confidence: 99%

“…MOTs are the first key components of the pipeline, which provide candidate detections of the players. Other components include team detection [52] or a combination of team and jersey identification [15]. The work by Maglo et al [30] uses detection followed by association of tracklets in sports videos using player re-identification.…”

Section: Related Workmentioning

confidence: 99%

Optimizing Long-Term Robot Tracking with Multi-Platform Sensor Fusion

Albanese,

Mitra,

Zaech

et al. 2024

2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)

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show abstract

“…In [21], a so-called tracklets constructed using a Kalman filter is defined as the representation of the trajectory of the detected object and is used to recognize each of the objects by utilizing player number recognition. Those aforementioned methods perform well in detection and uniquely identify objects.…”

Section: Related Workmentioning

confidence: 99%

“…A sophisticated method has been developed in [22] for basketball video by utilizing MSER, SIFT, and RGB color histograms altogether that is more robust compared to the other reviewed methods. However, the detection of objects during occlusion is not fully obtained, especially in [20] possibly when the occlusion occurred for objects with the same color; and in [21] due to incorrect player number recognition.…”

Section: Related Workmentioning

confidence: 99%

Automatic Soccer Player Tracking in Single Camera with Robust Occlusion Handling Using Attribute Matching

Sabirin

Suzuki

Naito

2015

IEICE Trans. Inf. & Syst.

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SUMMARYThis paper presents an automatic method to track soccer players in soccer video recorded from a single camera where the occurrence of pan-tilt-zoom can take place. The automatic object tracking is intended to support texture extraction in a free viewpoint video authoring application for soccer video. To ensure that the identity of the tracked object can be correctly obtained, background segmentation is performed and automatically removes commercial billboards whenever it overlaps with the soccer player. Next, object tracking is performed by an attribute matching algorithm for all objects in the temporal domain to find and maintain the correlation of the detected objects. The attribute matching process finds the best match between two objects in different frames according to their pre-determined attributes: position, size, dominant color and motion information. Utilizing these attributes, the experimental results show that the tracking process can handle occlusion problems such as occlusion involving more than three objects and occluded objects with similar color and moving direction, as well as correctly identify objects in the presence of camera movements. key words: free viewpoint, attribute matching, automatic object tracking, soccer video

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Tracking of Soccer Players Using Optical Flow

Kagalagomb

Dixit²

2020

Advances in Intelligent Systems and Computing

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Multiple players tracking and identification using group detection and player number recognition in sports video

Cited by 13 publications

References 6 publications

Optimizing Long-Term Robot Tracking with Multi-Platform Sensor Fusion

Optimizing Long-Term Robot Tracking with Multi-Platform Sensor Fusion

Automatic Soccer Player Tracking in Single Camera with Robust Occlusion Handling Using Attribute Matching

Tracking of Soccer Players Using Optical Flow

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