標(biāo)題: Titlebook: Computer Vision in Sports; Thomas B. Moeslund,Graham Thomas,Adrian Hilton Book 2014 Springer International Publishing Switzerland 2014 Com [打印本頁] 作者: 爆裂 時(shí)間: 2025-3-21 19:11
書目名稱Computer Vision in Sports影響因子(影響力)
書目名稱Computer Vision in Sports影響因子(影響力)學(xué)科排名
書目名稱Computer Vision in Sports網(wǎng)絡(luò)公開度
書目名稱Computer Vision in Sports網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Computer Vision in Sports被引頻次
書目名稱Computer Vision in Sports被引頻次學(xué)科排名
書目名稱Computer Vision in Sports年度引用
書目名稱Computer Vision in Sports年度引用學(xué)科排名
書目名稱Computer Vision in Sports讀者反饋
書目名稱Computer Vision in Sports讀者反饋學(xué)科排名
作者: glowing 時(shí)間: 2025-3-21 21:07 作者: inconceivable 時(shí)間: 2025-3-22 00:44 作者: septicemia 時(shí)間: 2025-3-22 04:47 作者: single 時(shí)間: 2025-3-22 11:27 作者: LAY 時(shí)間: 2025-3-22 13:01
Detecting and Tracking Sports Players with Random Forests and Context-Conditioned Motion Models degrees of freedom to represent the full motion diversity of each player and could be difficult to use in practice. Instead, we introduce a set of . extracted from noisy detection data to describe the current state of the match, such as how the players are spatially distributed. Our assumption is t作者: LAY 時(shí)間: 2025-3-22 18:46 作者: 蓋他為秘密 時(shí)間: 2025-3-22 22:08
Estimating Athlete Pose from Monocular TV Sports Footagerithms and probabilistic prior models based on learned measurements. Such algorithms face challenges in generalisation beyond the learned dataset. We propose an interactive model-based generative approach for estimating the human pose from uncalibrated monocular video in unconstrained sports TV foot作者: intolerance 時(shí)間: 2025-3-23 03:08 作者: 協(xié)定 時(shí)間: 2025-3-23 07:40 作者: Commentary 時(shí)間: 2025-3-23 11:49 作者: Circumscribe 時(shí)間: 2025-3-23 16:54 作者: 暗指 時(shí)間: 2025-3-23 19:30
Recognizing Team Formation in American Footballport in the United States, most American football game analysis is still done manually. Line of scrimmage and offensive team formation recognition are two statistics that must be tagged by American Football coaches when watching and evaluating past play video clips, a process which takes many man ho作者: 脆弱么 時(shí)間: 2025-3-24 01:28
Real-Time Event Detection in Field Sport Videosts. Using two independent event detection approaches that work simultaneously, the system is capable of accurately detecting scores, near misses, and other exciting parts of a game that do not result in a score. The results obtained across a diverse dataset of different field sports are promising, d作者: Reservation 時(shí)間: 2025-3-24 05:56 作者: 靦腆 時(shí)間: 2025-3-24 09:44
Book 2014ysis and classification of sports play. The insights provided by this pioneering collection will be of great interest to researchers and practitioners involved in computer vision, sports analysis and media production.作者: meritorious 時(shí)間: 2025-3-24 12:06
Jitter and Phase Noise in Ring Oscillators,y based on the amount of detail available in the video streams. These methods are complementary to each other and together provides a more complete set of tools for novel-view synthesis for sport broadcasts.作者: Inflamed 時(shí)間: 2025-3-24 15:19 作者: CLAN 時(shí)間: 2025-3-24 21:44 作者: 尊重 時(shí)間: 2025-3-25 02:18 作者: 釘牢 時(shí)間: 2025-3-25 03:49 作者: CALL 時(shí)間: 2025-3-25 11:15 作者: 慢慢沖刷 時(shí)間: 2025-3-25 13:50
The Design of Low Noise Oscillatorsage. Belief propagation over a spatio-temporal graph of candidate body part hypotheses is used to estimate a temporally consistent pose between user-defined keyframe constraints. Experimental results show that the proposed generative pose estimation framework is capable of estimating pose even in very challenging unconstrained scenarios.作者: 四目在模仿 時(shí)間: 2025-3-25 19:03
Book 2014in the application of computer vision to problems in sports. Opening with a detailed introduction to the use of computer vision across the entire life-cycle of a sports event, the text then progresses to examine cutting-edge techniques for tracking the ball, obtaining the whereabouts and pose of the作者: Anticonvulsants 時(shí)間: 2025-3-25 21:54
2191-6586 tracking, player tracking and pose estimation, and the detecThe first book of its kind devoted to this topic, this comprehensive text/reference presents state-of-the-art research and reviews current challenges in the application of computer vision to problems in sports. Opening with a detailed intro作者: 消毒 時(shí)間: 2025-3-26 03:49
https://doi.org/10.1007/BFb0017806enges, and propose a layered data association algorithm for tracking multiple tennis balls fully automatically. The effectiveness of the proposed algorithm is demonstrated on two data sets with more than 100 sequences from real-world tennis videos, where other data association methods perform poorly or fail completely.作者: BATE 時(shí)間: 2025-3-26 06:22 作者: 攀登 時(shí)間: 2025-3-26 08:33
Ball Tracking for Tennis Video Annotationenges, and propose a layered data association algorithm for tracking multiple tennis balls fully automatically. The effectiveness of the proposed algorithm is demonstrated on two data sets with more than 100 sequences from real-world tennis videos, where other data association methods perform poorly or fail completely.作者: Engaging 時(shí)間: 2025-3-26 16:30
Real-Time Event Detection in Field Sport Videosother exciting parts of a game that do not result in a score. The results obtained across a diverse dataset of different field sports are promising, demonstrating over 90?% accuracy for a feature-based event detector and 100?% accuracy for a scoreboard-based detector detecting only scores.作者: sperse 時(shí)間: 2025-3-26 17:46
https://doi.org/10.1007/978-3-319-09396-3Computer Vision; Human Activity and Behavior; Image and Video Analysis; Machine Learning; People Detecti作者: 不在灌木叢中 時(shí)間: 2025-3-26 21:13 作者: optional 時(shí)間: 2025-3-27 02:58 作者: Favorable 時(shí)間: 2025-3-27 09:11
The Design of Intelligent Agentslining some of these applications, giving examples of what is already being used, and referring to the relevant chapters later in the book where current research is presented. It then goes on to discuss the main themes covered by these chapters, and how they relate to each other.作者: 命令變成大炮 時(shí)間: 2025-3-27 11:28
Introduction to the Use of Computer Vision in Sports,lining some of these applications, giving examples of what is already being used, and referring to the relevant chapters later in the book where current research is presented. It then goes on to discuss the main themes covered by these chapters, and how they relate to each other.作者: Feedback 時(shí)間: 2025-3-27 17:12 作者: HARD 時(shí)間: 2025-3-27 20:45 作者: Foreshadow 時(shí)間: 2025-3-27 23:59 作者: 豐富 時(shí)間: 2025-3-28 02:13 作者: Outspoken 時(shí)間: 2025-3-28 09:35
https://doi.org/10.1007/978-3-642-82122-6ventional analysis in table tennis. There are methods of reconstructing 2D ball trajectories or 3D trajectories of balls heavier than those in table tennis. However, these methods cannot be adopted to reconstruct the 3D trajectories of table tennis balls, because there are problems that are attribut作者: 討厭 時(shí)間: 2025-3-28 13:25 作者: evasive 時(shí)間: 2025-3-28 14:39 作者: patella 時(shí)間: 2025-3-28 22:33
https://doi.org/10.1007/b101822 degrees of freedom to represent the full motion diversity of each player and could be difficult to use in practice. Instead, we introduce a set of . extracted from noisy detection data to describe the current state of the match, such as how the players are spatially distributed. Our assumption is t作者: Schlemms-Canal 時(shí)間: 2025-3-28 23:10 作者: FLAX 時(shí)間: 2025-3-29 06:33
The Design of Low Noise Oscillatorsrithms and probabilistic prior models based on learned measurements. Such algorithms face challenges in generalisation beyond the learned dataset. We propose an interactive model-based generative approach for estimating the human pose from uncalibrated monocular video in unconstrained sports TV foot作者: FECT 時(shí)間: 2025-3-29 10:01
Frequency Instability Fundamentals,search topics in this context. In this chapter, we provide a detailed study of the prominent methods devised for these two tasks which yield superior results for sports videos. We adopt UCF Sports, which is a dataset of realistic sports videos collected from broadcast television channels, as our eva作者: Exclude 時(shí)間: 2025-3-29 12:25
https://doi.org/10.1007/b101822uced from position data and is robust to detection noise. To overcome privacy issues when capturing video in public sports arenas we use thermal imaging only. This image modality also facilitates easier detection of humans; the detection algorithm is based on automatic thresholding of the image. Aft作者: Pulmonary-Veins 時(shí)間: 2025-3-29 18:01 作者: Abominate 時(shí)間: 2025-3-29 22:51
Frequency Instability Fundamentals,he players to be instrumented for each match. Unfortunately however, due to the heavy occlusion between players, variation in resolution and pose, in addition to fluctuating illumination conditions, tracking players continuously is still an unsolved vision problem. For tasks like clustering and retr作者: 神化怪物 時(shí)間: 2025-3-30 02:36
https://doi.org/10.1007/b101822port in the United States, most American football game analysis is still done manually. Line of scrimmage and offensive team formation recognition are two statistics that must be tagged by American Football coaches when watching and evaluating past play video clips, a process which takes many man ho作者: PANT 時(shí)間: 2025-3-30 06:31
Trends Toward Low-Voltage Power Supplies,ts. Using two independent event detection approaches that work simultaneously, the system is capable of accurately detecting scores, near misses, and other exciting parts of a game that do not result in a score. The results obtained across a diverse dataset of different field sports are promising, d作者: Pessary 時(shí)間: 2025-3-30 12:05
2191-6586 n will be of great interest to researchers and practitioners involved in computer vision, sports analysis and media production.978-3-319-37973-9978-3-319-09396-3Series ISSN 2191-6586 Series E-ISSN 2191-6594 作者: 有特色 時(shí)間: 2025-3-30 14:15
https://doi.org/10.1007/978-3-642-82122-6y demonstrated that it could provide accurate information for match analysis. A system using an RGB-D camera was experimentally demonstrated that the system could provide accurate information for service analysis.作者: AWRY 時(shí)間: 2025-3-30 18:57 作者: 沉默 時(shí)間: 2025-3-31 00:15 作者: 極小 時(shí)間: 2025-3-31 03:03
https://doi.org/10.1007/b101822while remaining tractable. We demonstrate significant performance improvements over existing multitarget tracking algorithms on basketball and field hockey sequences of several minutes in duration containing 10 and 20 players, respectively.作者: 凝乳 時(shí)間: 2025-3-31 05:24 作者: dowagers-hump 時(shí)間: 2025-3-31 09:32
Frequency Instability Fundamentals,ough is that the compressibility is low (i.e. the variability in the feature space is incredibly high). In this paper, we propose the use of a bilinear spatiotemporal basis model using a . to clean-up the noisy detections which operates in a low-dimensional space. To evaluate our approach, we used a作者: FLAT 時(shí)間: 2025-3-31 15:16
https://doi.org/10.1007/b101822d framework achieves 95?% accuracy in detecting the formation frame, 98?% accuracy in detecting the line of scrimmage, and up?to 67?% accuracy in classifying the offensive team’s formation. To validate our framework, we compiled a large dataset comprising more than 800 play-clips of standard and hig
