17.1.3.8.9 Human Activities, Sports, Summaries, Highlights

Chapter Contents (Back)
Activity Recognition. Sports. Highlights.
See also Basketball Tracking, Desctiptions, Line Judge.
See also Tennis Tracking, Desctiptions, Line Judge.
See also Baseball, Cricket, Tracking, Desctiptions, Analysis.
See also Football, Soccer, Tracking, Desctiptions, Analysis.

On Demand Real Time, LiveClips,
2011
WWW Link. Vendor, Sports Highlights. Provide the clips the user wants using computer vision analysis.

Lu, H.[Hong], Tan, Y.P.[Yap-Peng],
Unsupervised clustering of dominant scenes in sports video,
PRL(24), No. 15, November 2003, pp. 2651-2662.
Elsevier DOI 0308
BibRef
Earlier: A2, A1:
Model-based clustering and analysis of video scenes,
ICIP02(I: 617-620).
IEEE DOI 0210
BibRef

Li, B.X.[Bao-Xin], Errico, J.H.[James H.], Pan, H.[Hao], Sezan, M.I.[M. Ibrahim],
Bridging the semantic gap in sports video retrieval and summarization,
JVCIR(15), No. 3, September 2004, pp. 393-424.
Elsevier DOI 0711
Semantic video analysis; Video summarization; Event detection BibRef

Li, B.X.[Bao-Xin], and Sezan, M.I.[M. Ibrahim],
Semantic sports video analysis: approaches and new applications,
ICIP03(I: 17-20).
IEEE DOI 0312
BibRef
Earlier:
Event Detection and Summarization in Sports Video,
CVPR01(Demos 29-30). 0110
BibRef
And: CBAIVL01(132).
IEEE DOI 0110
BibRef

Li, B.X.[Bao-Xin],
Summarization of Sumo Video Content,
US_Patent7,120,873, Oct 10, 2006
WWW Link. BibRef 0610

Li, B.X.[Bao-Xin], Sampsell, J.B.[Jeffrey B.],
Summarization of Baseball Video Content,
US_Patent7,143,354, Nov 28, 2006
WWW Link. BibRef 0611

Li, B.X.[Bao-Xin],
Summarization of video content,
US_Patent7,203,620, Apr 10, 2007
WWW Link. BibRef 0704
And:
Processing of video content,
US_Patent7,006,945, Feb 28, 2006
WWW Link. BibRef
And: US_Patent7,047,157, May 16, 2006
WWW Link. BibRef
And: US_Patent7,310,589, Dec 18, 2007
WWW Link. BibRef US_Patent7,167,809, Jan 23, 2007
WWW Link. BibRef

Suh, J.Y.[Jong Yeul],
Apparatus for automatically generating video highlights and method thereof,
US_Patent7,199,841, Apr 3, 2007
WWW Link. BibRef 0704

Nitta, N.[Naoko], Babaguchi, N.[Noboru],
User and Device Adaptation in Summarizing Sports Videos,
IEICE(E92-D), No. 6, June 2009, pp. 1280-1288.
WWW Link. 0907
BibRef

Nitta, N.[Naoko], Babaguchi, N.[Noboru], Kitahashi, T.,
Extracting Actors, Actions and Events from Sports Video: A Fundamental Approach to Story Tracking,
ICPR00(Vol IV: 718-721).
IEEE DOI 0009
BibRef

Babaguchi, N.[Noboru],
Towards Abstracting Sports Video by Highlights,
ICME00(WP5). 0007
BibRef

Chen, F.[Fan], de Vleeschouwer, C.[Christophe],
Formulating Team-Sport Video Summarization as a Resource Allocation Problem,
CirSysVideo(21), No. 2, February 2011, pp. 193-205.
IEEE DOI 1103
BibRef
Earlier:
A resource allocation framework for summarizing team sport videos,
ICIP09(4349-4352).
IEEE DOI 0911
BibRef

Patrikakis, C.Z.[Charalampos Z.], Papaoulakis, N.[Nikolaos], Papageorgiou, P.[Panagiotis], Pnevmatikakis, A.[Aristodemos], Chippendale, P.[Paul], Nunes, M.[Mario], Cruz, R.S.[Rui Santos], Poslad, S.[Stefan], Wang, Z.C.[Zhen-Chen],
Personalized Coverage of Large Athletic Events,
MultMedMag(18), No. 4, October-December 2011, pp. 18-29.
IEEE DOI 1112
BibRef

Ouyang, J.Q.[Jian-Quan], Liu, R.R.[Ren-Ren],
Ontology reasoning scheme for constructing meaningful sports video summarisation,
IET-IPR(7), No. 4, 2013, pp. 324-334.
DOI Link 1307
BibRef

Sainio, J.[Jani], Westerholm, J.[Jan], Oksanen, J.[Juha],
Generating Heat Maps of Popular Routes Online from Massive Mobile Sports Tracking Application Data in Milliseconds While Respecting Privacy,
IJGI(4), No. 4, 2015, pp. 1813.
DOI Link 1511
BibRef

Javed, A., Bajwa, K.B., Malik, H., Irtaza, A.,
An Efficient Framework for Automatic Highlights Generation from Sports Videos,
SPLetters(23), No. 7, July 2016, pp. 954-958.
IEEE DOI 1608
computational complexity BibRef

Turchini, F.[Francesco], Seidenari, L.[Lorenzo], del Bimbo, A.[Alberto],
Understanding and localizing activities from correspondences of clustered trajectories,
CVIU(159), No. 1, 2017, pp. 128-142.
Elsevier DOI 1706
BibRef
Earlier:
Understanding Sport Activities from Correspondences of Clustered Trajectories,
CVSports15(760-767)
IEEE DOI 1602
Action recognition. Computer vision BibRef

Kasiri-Bidhendi, S.[Soudeh], Fookes, C.[Clinton], Sridharan, S.[Sridha], Morgan, S.[Stuart],
Fine-grained action recognition of boxing punches from depth imagery,
CVIU(159), No. 1, 2017, pp. 143-153.
Elsevier DOI 1706
Fine-grained, action, recognition BibRef

Boukadida, H.[Haykel], Berrani, S.A.[Sid-Ahmed], Gros, P.[Patrick],
Automatically Creating Adaptive Video Summaries Using Constraint Satisfaction Programming: Application to Sport Content,
CirSysVideo(27), No. 4, April 2017, pp. 920-934.
IEEE DOI 1704
BibRef
Earlier:
A Novel Modeling for Video Summarization Using Constraint Satisfaction Programming,
ISVC14(II: 208-219).
Springer DOI 1501
BibRef

Kasiri-Bidhendi, S.[Soudeh], Fookes, C.[Clinton], Morgan, S.[Stuart], Martin, D.T.[David T.], Sridharan, S.[Sridha],
Combat sports analytics: Boxing punch classification using overhead depth imagery,
ICIP15(4545-4549)
IEEE DOI 1512
Sports analytics; body part detection; boxing; punch classification BibRef

Jiao, Y.F.[Yi-Fan], Li, Z.T.[Zhe-Tao], Huang, S.C.[Shu-Cheng], Yang, X.S.[Xiao-Shan], Liu, B.[Bin], Zhang, T.Z.[Tian-Zhu],
Three-Dimensional Attention-Based Deep Ranking Model for Video Highlight Detection,
MultMed(20), No. 10, October 2018, pp. 2693-2705.
IEEE DOI 1810
feature extraction, image segmentation, learning (artificial intelligence), neural nets, deep ranking BibRef

Jiao, Y.F.[Yi-Fan], Yang, X.S.[Xiao-Shan], Zhang, T.Z.[Tian-Zhu], Huang, S.C.[Shu-Cheng], Xu, C.S.[Chang-Sheng],
Video Highlight Detection via Deep Ranking Modeling,
PSIVT17(28-39).
Springer DOI 1802
BibRef

Tejero-de-Pablos, A., Nakashima, Y.[Yuta], Sato, T., Yokoya, N.[Naokazu], Linna, M., Rahtu, E.[Esa],
Summarization of User-Generated Sports Video by Using Deep Action Recognition Features,
MultMed(20), No. 8, August 2018, pp. 2000-2011.
IEEE DOI 1808
feature extraction, image segmentation, neural nets, sport, video signal processing, high-level semantics, long short-term memory BibRef

Otani, M.[Mayu], Nakashima, Y.[Yuta], Rahtu, E.[Esa], Heikkilä, J.[Janne], Yokoya, N.[Naokazu],
Video Summarization Using Deep Semantic Features,
ACCV16(V: 361-377).
Springer DOI 1704
BibRef

Chen, S., Jin, Q., Chen, J., Hauptmann, A.G.,
Generating Video Descriptions With Latent Topic Guidance,
MultMed(21), No. 9, September 2019, pp. 2407-2418.
IEEE DOI 1909
Task analysis, Decoding, Predictive models, Sports, Acoustics, Visualization, Semantics, Video Captioning, Latent Topic, Multimodal Ensemble BibRef

Merler, M., Mac, K.C., Joshi, D., Nguyen, Q.B., Hammer, S., Kent, J., Xiong, J., Do, M.N., Smith, J.R., Feris, R.S.,
Automatic Curation of Sports Highlights Using Multimodal Excitement Features,
MultMed(21), No. 5, May 2019, pp. 1147-1160.
IEEE DOI 1905
BibRef
Earlier: A1, A3, A4, A5, A6, A9, A10, Only:
Automatic Curation of Golf Highlights Using Multimodal Excitement Features,
CVSports17(57-65)
IEEE DOI 1709
feature extraction, information retrieval, learning (artificial intelligence), meta data, multimodal video analysis. Games, TV, Training, Training data, Visualization BibRef

Mac, K.C., Joshi, D., Yeh, R., Xiong, J., Feris, R.S., Do, M.N.,
Learning Motion in Feature Space: Locally-Consistent Deformable Convolution Networks for Fine-Grained Action Detection,
ICCV19(6281-6290)
IEEE DOI 2004
convolutional neural nets, feature extraction, Deformable models, image motion analysis, learning (artificial intelligence). BibRef

Liu, Z.K.[Zhen-Kun],
3DSportNet: 3D sport reconstruction by quality-aware deep multi-video summation,
JVCIR(65), 2019, pp. 102651.
Elsevier DOI 1912
3D reconstruction, Quality model, Weakly-supervised learning BibRef

Vats, K., Fani, M., Walters, P., Clausi, D.A., Zelek, J.,
Event detection in coarsely annotated sports videos via parallel multi receptive field 1D convolutions,
CVSports20(3856-3865)
IEEE DOI 2008
Videos, Poles and towers, Event detection, Games, Task analysis, Computer vision BibRef

Qi, M., Wang, Y., Li, A., Luo, J.,
Sports Video Captioning via Attentive Motion Representation and Group Relationship Modeling,
CirSysVideo(30), No. 8, August 2020, pp. 2617-2633.
IEEE DOI 2008
Sports, Visualization, Trajectory, Semantics, Task analysis, Logic gates, Games, Sports video, video captioning, RNN BibRef

Liu, A.A.[An-An], Zhai, Y.C.[Ying-Chen], Xu, N.[Ning], Nie, W.Z.[Wei-Zhi], Li, W.H.[Wen-Hui], Zhang, Y.D.[Yong-Dong],
Region-Aware Image Captioning via Interaction Learning,
CirSysVideo(32), No. 6, June 2022, pp. 3685-3696.
IEEE DOI 2206
Visualization, Semantics, Task analysis, Proposals, Learning systems, Sports, Feature extraction, Region modeling, interaction learning, image captioning BibRef

Askari, F.[Farzaneh], Ramaprasad, R.[Rohit], Clark, J.J.[James J.], Levine, M.D.[Martin D.],
Interaction Classification with Key Actor Detection in Multi-Person Sports Videos,
CVSports22(3579-3587)
IEEE DOI 2210
Visualization, Recurrent neural networks, Annotations, Computational modeling, Ice, Recording BibRef

Chen, W.[Wei], Liu, X.F.[Xue-Feng], Niu, J.W.[Jian-Wei],
SentiStory: A Multi-Layered Sentiment-Aware Generative Model for Visual Storytelling,
CirSysVideo(32), No. 11, November 2022, pp. 8051-8064.
IEEE DOI 2211
Visualization, Optimized production technology, Streaming media, Task analysis, Pediatrics, Generators, Sports, Visual storytelling, coherence BibRef


Ferreira, B.[Bruno], Menezes, P.[Paulo], Batista, J.[Jorge],
Transformers for Workout Video Segmentation,
ICIP22(3470-3474)
IEEE DOI 2211
Image segmentation, Motion segmentation, Pipelines, Neural networks, Manuals, Multilayer perceptrons, Transformers, Exercise repetition analysis BibRef

Wu, D.K.[De-Kun], Zhao, H.[He], Bao, X.C.[Xing-Ce], Wildes, R.P.[Richard P.],
Sports Video Analysis on Large-Scale Data,
ECCV22(XXXVII:19-36).
Springer DOI 2211
BibRef

Badamdorj, T.[Taivanbat], Rochan, M.[Mrigank], Wang, Y.[Yang], Cheng, L.[Li],
Contrastive Learning for Unsupervised Video Highlight Detection,
CVPR22(14022-14032)
IEEE DOI 2210
Training, Annotations, Benchmark testing, Data models, Pattern recognition, Video analysis and understanding, Self- semi- meta- Vision applications and systems BibRef

Wei, F.[Fanyue], Wang, B.[Biao], Ge, T.[Tiezheng], Jiang, Y.N.[Yu-Ning], Li, W.[Wen], Duan, L.X.[Li-Xin],
Learning Pixel-Level Distinctions for Video Highlight Detection,
CVPR22(3063-3072)
IEEE DOI 2210
Visualization, Solid modeling, Computational modeling, Benchmark testing, Pattern recognition, Video analysis and understanding BibRef

Liu, Y.[Ye], Li, S.Y.[Si-Yuan], Wu, Y.[Yang], Chen, C.W.[Chang Wen], Shan, Y.[Ying], Qie, X.[Xiaohu],
UMT: Unified Multi-modal Transformers for Joint Video Moment Retrieval and Highlight Detection,
CVPR22(3032-3041)
IEEE DOI 2210
Video on demand, Natural languages, 3G mobile communication, Transformers, Generators, Pattern recognition, Proposals, retrieval BibRef

Chen, R.[Runnan], Zhou, P.H.[Peng-Hao], Wang, W.Z.[Wen-Zhe], Chen, N.L.[Neng-Lun], Peng, P.[Pai], Sun, X.[Xing], Wang, W.P.[Wen-Ping],
PR-Net: Preference Reasoning for Personalized Video Highlight Detection,
ICCV21(7960-7969)
IEEE DOI 2203
Annotations, Semantics, Extraterrestrial measurements, Cognition, History, Video analysis and understanding, BibRef

Rahimi, A.M.[Amir M.], Lee, K.[Kevin], Agarwal, A.[Amit], Kwon, H.[Hyukseong], Bhattacharyya, R.[Rajan],
Toward Improving The Visual Characterization of Sport Activities With Abstracted Scene Graphs,
CVSports21(4495-4502)
IEEE DOI 2109
Training, Visualization, Uncertainty, Semantics, Performance gain, Search problems, Task analysis BibRef

Tanaka, T.[Tsunehiko], Simo-Serra, E.[Edgar],
LoL-V2T: Large-Scale Esports Video Description Dataset,
CVSports21(4552-4561)
IEEE DOI 2109
Training, Vocabulary, Video description, Focusing, Games BibRef

Hong, F.T.[Fa-Ting], Huang, X.T.[Xuan-Teng], Li, W.H.[Wei-Hong], Zheng, W.S.[Wei-Shi],
Mini-Net: Multiple Instance Ranking Network for Video Highlight Detection,
ECCV20(XIII:345-360).
Springer DOI 2011
BibRef

Spijkerman, R.[Ruan], van der Haar, D.[Dustin],
Video Footage Highlight Detection in Formula 1 Through Vehicle Recognition with Faster R-cnn Trained on Game Footage,
ICCVG20(176-187).
Springer DOI 2009
BibRef

Patsiouras, E., Tefas, A., Pitas, I.,
Few-shot Image Recognition for UAV Sports Cinematography,
CLVision20(965-969)
IEEE DOI 2008
Training, Image recognition, Task analysis, Visualization, Standards, Computational modeling, few-shot learning, image recognition, unmaned aerial vehicles BibRef

Lee, H., Lee, G.,
Hierarchical Model For Long-Length Video Summarization With Adversarially Enhanced Audio/Visual Features,
ICIP20(723-727)
IEEE DOI 2011
BibRef
Earlier:
Summarizing Long-Length Videos with GAN-Enhanced Audio/Visual Features,
MMVAMTC19(3727-3731)
IEEE DOI 2004
Visualization, Feature extraction, Semantics, Benchmark testing, Task analysis, Generators, video summarization, long-length videos. audio signal processing, sport, video signal processing, supervised method, Multimodal BibRef

Song, Z.K.[Zi-Kai], Yu, J.Q.[Jun-Qing], Cai, H.Y.[Heng-You], Hu, Y.L.[Yang-Liu], Chen, Y.P.P.[Yi-Ping Phoebe],
Fine-grain Level Sports Video Search Engine,
MMMod20(I:519-531).
Springer DOI 2003
BibRef

Patrona, F., Mademlis, I., Tefas, A., Pitas, I.,
Computational UAV Cinematography for Intelligent Shooting Based on Semantic Visual Analysis,
ICIP19(4155-4159)
IEEE DOI 1910
autonomous UAVs, cinematography, sports broadcasting, human-centered visual analysis, PID controller BibRef

Wang, H., Yu, H., Chen, P., Hua, R., Yan, C., Zou, L.,
Unsupervised Video Highlight Extraction via Query-related Deep Transfer,
ICPR18(2971-2976)
IEEE DOI 1812
Feature extraction, Semantics, Visualization, Search engines, Adaptation models, Computational modeling, Training BibRef

Gupta, N., Jain, A., Agarwal, P., Mujumdar, S., Mehta, S.,
Pentuplet Loss for Simultaneous Shots and Critical Points Detection in a Video,
ICPR18(2392-2397)
IEEE DOI 1812
Sports, Task analysis, Measurement, Optimization, Feature extraction, Training BibRef

Kaichi, T., Mori, S., Saito, H., Takahashi, K., Mikami, D., Isogawa, M., Kimata, H.,
Estimation of Center of Mass for Sports Scene Using Weighted Visual Hull,
CVSports18(1890-18906)
IEEE DOI 1812
Force, Estimation, Sports, Solid modeling, Cameras BibRef

Wang, W., Shen, J., Guo, F., Cheng, M., Borji, A.,
Revisiting Video Saliency: A Large-Scale Benchmark and a New Model,
CVPR18(4894-4903)
IEEE DOI 1812
Sports, Task analysis, Benchmark testing, Dynamics, Observers, Computational modeling, Video sequences BibRef

Fayyaz, M., Gall, J.,
SCT: Set Constrained Temporal Transformer for Set Supervised Action Segmentation,
CVPR20(498-507)
IEEE DOI 2008
Training, Hidden Markov models, Kernel, Task analysis, Supervised learning, Convolution, Context modeling BibRef

Richard, A., Kuehne, H., Gall, J.,
Action Sets: Weakly Supervised Action Segmentation Without Ordering Constraints,
CVPR18(5987-5996)
IEEE DOI 1812
Videos, Context modeling, Task analysis, Labeling, Training, Mathematical model, Feature extraction BibRef

Farha, Y.A., Richard, A., Gall, J.,
When will you do what? - Anticipating Temporal Occurrences of Activities,
CVPR18(5343-5352)
IEEE DOI 1812
Videos, Training, Task analysis, Matrix converters, Visualization, Sports, Labeling BibRef

Yu, H., Cheng, S., Ni, B., Wang, M., Zhang, J., Yang, X.,
Fine-Grained Video Captioning for Sports Narrative,
CVPR18(6006-6015)
IEEE DOI 1812
Sports, Task analysis, Skeleton, Feature extraction, Adaptive optics, Optical pulses, Measurement BibRef

Gu, C., Sun, C., Ross, D.A., Vondrick, C., Pantofaru, C., Li, Y., Vijayanarasimhan, S., Toderici, G., Ricco, S., Sukthankar, R., Schmid, C., Malik, J.,
AVA: A Video Dataset of Spatio-Temporally Localized Atomic Visual Actions,
CVPR18(6047-6056)
IEEE DOI 1812
Motion pictures, Visualization, Vocabulary, Sports, YouTube, Labeling, Detectors BibRef

Doughty, H., Damen, D., Mayol-Cuevas, W.,
Who's Better? Who's Best? Pairwise Deep Ranking for Skill Determination,
CVPR18(6057-6066)
IEEE DOI 1812
Task analysis, Surgery, Training, Sports, Video sequences, Distance measurement, Neural networks BibRef

Hu, H.N., Lin, Y.C., Liu, M.Y., Cheng, H.T., Chang, Y.J., Sun, M.,
Deep 360 Pilot: Learning a Deep Agent for Piloting through 360 deg; Sports Videos,
CVPR17(1396-1405)
IEEE DOI 1711
Cameras, Cinematography, Detectors, Navigation, Pipelines, Videos BibRef

Itazuri, T., Fukusato, T., Yamaguchi, S., Morishima, S.,
Court-Based Volleyball Video Summarization Focusing on Rally Scene,
CVSports17(179-186)
IEEE DOI 1709
Cameras, Computational modeling, Correlation, Event detection, Feature extraction, Games, Robustness BibRef

Nibali, A., He, Z., Morgan, S., Greenwood, D.,
Extraction and Classification of Diving Clips from Continuous Video Footage,
CVSports17(94-104)
IEEE DOI 1709
Agriculture, Feature extraction, Monitoring, Object tracking, Training BibRef

Xue, Y., Song, Y., Li, C., Chiang, A.T., Ning, X.,
Automatic Video Annotation System for Archival Sports Video,
SoftBio17(23-28)
IEEE DOI 1609
image representation, object detection, object tracking, optical character recognition, sport, video signal processing, OCR, archival sports broadcast videos, BibRef

Gade, R., Abou-Zleikha, M., Christensen, M.G., Moeslund, T.B.,
Audio-Visual Classification of Sports Types,
CVSports15(768-773)
IEEE DOI 1602
Cameras BibRef

Hasegawa, K., Saito, H.,
Stroboscopic Image Synthesis of Sports Player from Hand-Held Camera Sequence,
CVSports15(726-733)
IEEE DOI 1602
Cameras BibRef

Jeon, J.[Jin], Kim, M.C.[Mun-Churl],
A spatial class LDA model for classification of sports scene images,
ICIP15(4649-4653)
IEEE DOI 1512
Bag-of-word; Image classification; LDA; Spatial information; Sports scene BibRef

Ntalianis, K.[Klimis], Tsapatsoulis, N.[Nicolas],
Unsupervised sports video particles annotation based on social latent semantic analysis,
ICIP15(222-226)
IEEE DOI 1512
Intelligent Wrapper BibRef

Xu, X.Z.[Xing-Zhong], Man, H.[Hong],
Interpreting sports tactic based on latent context-free grammar,
ICIP15(4072-4076)
IEEE DOI 1512
semantic parsing; sports video analysis; stochastic context-free Grammar BibRef

Stenhaug, M.[Magnus], Yang, Y.[Yang], Gurrin, C.[Cathal], Johansen, D.[Dag],
Muithu: A Touch-Based Annotation Interface for Activity Logging in the Norwegian Premier League,
MMMod14(II: 365-368).
Springer DOI 1405
BibRef

Aoki, K.[Kyota], Fukiba, T.[Takuro],
Play Estimation with Motions and Textures in Space-Time Map Description,
DevCen12(I:279-290).
Springer DOI 1304
small parts of large videos. BibRef

Yan, F.[Fei], Kittler, J.V.[Josef V.], Mikolajczyk, K.[Krystian], Windridge, D.[David],
Automatic annotation of court games with structured output learning,
ICPR12(3577-3580).
WWW Link. 1302
BibRef

Ghanem, B.[Bernard], Kreidieh, M.[Maya], Farra, M.[Marc], Zhang, T.Z.[Tian-Zhu],
Context-aware learning for automatic sports highlight recognition,
ICPR12(1977-1980).
WWW Link. 1302
BibRef

Tjondronegoro, D.[Dian], Tao, X.H.[Xiao-Hui], Sasongko, J.[Johannes], Lau, C.H.[Cher Han],
Multi-modal summarization of key events and top players in sports tournament videos,
WACV11(471-478).
IEEE DOI 1101
BibRef

Chapter on Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities continues in
Football, Soccer, Tracking, Desctiptions, Analysis .


Last update:Mar 16, 2024 at 20:36:19