{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,2]],"date-time":"2026-10-02T10:24:40Z","timestamp":1790936680996,"version":"4.1.0"},"publisher-location":"New York, NY, USA","reference-count":34,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,6,10]],"date-time":"2022-06-10T00:00:00Z","timestamp":1654819200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Institute of Information & Communications Technology Planning & Evaluation (IITP)","award":["No. 2021-0-00766"],"award-info":[{"award-number":["No. 2021-0-00766"]}]},{"DOI":"10.13039\/100000001","name":"NSF (National Science Foundation)","doi-asserted-by":"publisher","award":["CNS-1815047;IIS-1850342;IIS-1908984"],"award-info":[{"award-number":["CNS-1815047;IIS-1850342;IIS-1908984"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,6,10]]},"DOI":"10.1145\/3514221.3517857","type":"proceedings-article","created":{"date-parts":[[2022,6,12]],"date-time":"2022-06-12T02:33:49Z","timestamp":1655001229000},"page":"559-572","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":35,"title":["FiGO: Fine-Grained Query Optimization in Video Analytics"],"prefix":"10.1145","author":[{"given":"Jiashen","family":"Cao","sequence":"first","affiliation":[{"name":"Georgia Institute of Technology, Atlanta, GA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Karan","family":"Sarkar","sequence":"additional","affiliation":[{"name":"Georgia Institute of Technology, Atlanta, GA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ramyad","family":"Hadidi","sequence":"additional","affiliation":[{"name":"Georgia Institute of Technology, Atlanta, GA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joy","family":"Arulraj","sequence":"additional","affiliation":[{"name":"Georgia Institute of Technology, Atlanta, GA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hyesoon","family":"Kim","sequence":"additional","affiliation":[{"name":"Georgia Institute of Technology, Atlanta, GA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2022,6,11]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"Shipra Agrawal and Navin Goyal. 2012. Analysis of thompson sampling for the multi-armed bandit problem. In COLT."},{"key":"e_1_3_2_1_2_1","volume-title":"Wenisch","author":"Anderson Michael R.","year":"2019","unstructured":"Michael R. Anderson, Michael Cafarella, German Ros, and Thomas F. Wenisch. 2019. Physical Representation -Based Predicate Optimization for a Visual Analytics Database. In ICDE. 1466--1477."},{"key":"e_1_3_2_1_3_1","volume-title":"MIRIS : Fast Object Track Queries in Video. In SIGMOD. 1907--1921.","author":"Bastani Favyen","year":"2020","unstructured":"Favyen Bastani, Songtao He, Arjun Balasingam, Karthik Gopalakrishnan, Mohammad Alizadeh, Hari Balakrishnan, Michael Cafarella, Tim Kraska, and Sam Madden. 2020. MIRIS : Fast Object Track Queries in Video. In SIGMOD. 1907--1921."},{"key":"e_1_3_2_1_4_1","unstructured":"Christopher Canel Thomas Kim Giulio Zhou Conglong Li Hyeontaek Lim David G Andersen Michael Kaminsky and Subramanya R Dulloor. 2019. Scaling Video Analytics on Constrained Edge Nodes. In SysML."},{"key":"e_1_3_2_1_5_1","unstructured":"Olivier Chapelle and Lihong Li. 2011. An Empirical Evaluation of Thompson Sampling. In NeurIPS."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"crossref","unstructured":"Jack Chen Samir Jindel Robert Walzer Rajkumar Sen Nika Jimsheleishvilli and Michael Andrews. 2016. The MemSQL Query Optimizer: A Modern Optimizer for Real-Time Analytics in a Distributed Database. In PVLDB. 1401--1412.","DOI":"10.14778\/3007263.3007277"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.5465\/amj.2006.22083026"},{"key":"e_1_3_2_1_8_1","volume-title":"VSS : A Storage System for Video Analytics. In SIGMOD. 685--696.","author":"Haynes Brandon","year":"2021","unstructured":"Brandon Haynes, Maureen Daum, Dong He, Amrita Mazumdar, Magdalena Balazinska, Alvin Cheung, and Luis Ceze. 2021. VSS : A Storage System for Video Analytics. In SIGMOD. 685--696."},{"key":"e_1_3_2_1_9_1","unstructured":"Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2015. Deep Residual Learning for Image Recognition. In CVPR. 770--778."},{"key":"e_1_3_2_1_10_1","volume-title":"Focus: Querying Large Video Datasets with Low Latency and Low Cost. In OSDI. 269--286.","author":"Hsieh Kevin","year":"2018","unstructured":"Kevin Hsieh, Ganesh Ananthanarayanan, Peter Bodik, Shivaram Venkataraman, Paramvir Bahl, Matthai Philipose, Phillip B Gibbons, and Onur Mutlu. 2018. Focus: Querying Large Video Datasets with Low Latency and Low Cost. In OSDI. 269--286."},{"key":"e_1_3_2_1_11_1","volume-title":"Sur les fonctions convexes et les in\u00e9galit\u00e9s entre les valeurs moyennes. Acta Mathematica","author":"Jensen J. L. W. V.","year":"1906","unstructured":"J. L. W. V. Jensen. 1906. Sur les fonctions convexes et les in\u00e9galit\u00e9s entre les valeurs moyennes. Acta Mathematica (1906), 175--193."},{"key":"e_1_3_2_1_12_1","volume-title":"Siddhartha Sen, and Ion Stoica.","author":"Jiang Junchen","year":"2018","unstructured":"Junchen Jiang, Ganesh Ananthanarayanan, Peter Bod'i k, Siddhartha Sen, and Ion Stoica. 2018. Chameleon: scalable adaptation of video analytics. In SIGCOMM. 253--266."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"crossref","unstructured":"Daniel Kang Peter Bailis and Matei Zaharia. 2019. BlazeIt: Optimizing Declarative Aggregation and Limit Queries for Neural Network-Based Video Analytics. In PVLDB. 533--546.","DOI":"10.14778\/3372716.3372725"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"crossref","unstructured":"Daniel Kang John Emmons Firas Abuzaid Peter Bailis and Matei Zaharia. 2017. NoScope: Optimizing Deep CNN-Based Queries over Video Streams at Scale. In PVLDB. 1586--1597.","DOI":"10.14778\/3137628.3137664"},{"key":"e_1_3_2_1_15_1","volume-title":"The multi-armed bandit problem: decomposition and computation. Mathematics of Operations Research","author":"Katehakis Michael N","year":"1987","unstructured":"Michael N Katehakis and Arthur F Veinott Jr. 1987. The multi-armed bandit problem: decomposition and computation. Mathematics of Operations Research (1987), 262--268."},{"key":"e_1_3_2_1_16_1","volume":"201","author":"Krishnan Sanjay","unstructured":"Sanjay Krishnan, Adam Dziedzic, and Aaron J Elmore. 2019. DeepLens : Towards a Visual Data Management System.","journal-title":"Aaron J Elmore."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"crossref","unstructured":"Tsung-Yi Lin Michael Maire Serge Belongie James Hays Pietro Perona Deva Ramanan Piotr Doll\u00e1r and C. Lawrence Zitnick. 2014. Microsoft COCO : Common Objects in Context. In ECCV. 740--755.","DOI":"10.1007\/978-3-319-10602-1_48"},{"key":"e_1_3_2_1_18_1","volume-title":"Berg","author":"Liu Wei","year":"2016","unstructured":"Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, and Alexander C. Berg. 2016. SSD : Single Shot MultiBox Detector. In ECCV. 21--37."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"crossref","unstructured":"Yao Lu Aakanksha Chowdhery Srikanth Kandula and Surajit Chaudhuri. 2018. Accelerating Machine Learning Inference with Probabilistic Predicates. In SIGMOD. 1493--1508.","DOI":"10.1145\/3183713.3183751"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1287\/orsc.2.1.71"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"crossref","unstructured":"Ryan Marcus Parimarjan Negi Hongzi Mao Chi Zhang Mohammad Alizadeh Tim Kraska Olga Papaemmanouil and Nesime Tatbul. 2019. Neo: a learned query optimizer. In PVLDB. 1705--1718.","DOI":"10.14778\/3342263.3342644"},{"key":"e_1_3_2_1_22_1","volume-title":"Efficient Searches on Video Repositories through Adaptive Sampling. arXiv:2005.09141 [cs]","author":"Moll Oscar","year":"2020","unstructured":"Oscar Moll, Favyen Bastani, Sam Madden, Mike Stonebraker, Vijay Gadepally, and Tim Kraska. 2020. ExSample : Efficient Searches on Video Repositories through Adaptive Sampling. arXiv:2005.09141 [cs] (2020)."},{"key":"e_1_3_2_1_23_1","unstructured":"Sangmin Oh Anthony Hoogs Amitha Perera Naresh Cuntoor Chia-Chih Chen Jong Taek Lee Saurajit Mukherjee J. K. Aggarwal Hyungtae Lee Larry Davis Eran Swears Xioyang Wang Qiang Ji Kishore Reddy Mubarak Shah Carl Vondrick Hamed Pirsiavash Deva Ramanan Jenny Yuen Antonio Torralba Bi Song Anesco Fong Amit Roy-Chowdhury and Mita Desai. 2011. A Large-Scale Benchmark Dataset for Event Recognition in Surveillance Video. In CVPR. 3153--3160."},{"key":"e_1_3_2_1_24_1","unstructured":"Adam Paszke Sam Gross Soumith Chintala Gregory Chanan Edward Yang Zachary DeVito Zeming Lin Alban Desmaison Luca Antiga and Adam Lerer. 2017. Automatic differentiation in PyTorch. In NeurIPS."},{"key":"e_1_3_2_1_25_1","unstructured":"Shaoqing Ren Kaiming He Ross B. Girshick and Jian Sun. 2015. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks. In NeurIPS. 91--99."},{"key":"e_1_3_2_1_26_1","volume-title":"Sect. Math","author":"Bernstein S.N.","year":"1924","unstructured":"S.N.Bernstein. 1924. On a modification of Chebyshev's inequality and of the error formula of Laplace. Ann. Sci. Inst. Sav. Ukraine, Sect. Math (1924)."},{"key":"e_1_3_2_1_27_1","unstructured":"Michael Stillger Guy Lohman Volker Markl and Mokhtar Kandil. 2001. LEO -- DB2's LEarning Optimizer. In PVLDB. 19--28."},{"key":"e_1_3_2_1_28_1","volume-title":"Le","author":"Tan Mingxing","year":"2020","unstructured":"Mingxing Tan, Ruoming Pang, and Quoc V. Le. 2020. EfficientDet: Scalable and Efficient Object Detection. In CVPR. 10778--10787."},{"key":"e_1_3_2_1_29_1","volume-title":"On the Likelihood That One Unknown Probability Exceeds Another in View of the Evidence of Two Samples. Biometrika","author":"Thompson William R.","year":"1933","unstructured":"William R. Thompson. 1933. On the Likelihood That One Unknown Probability Exceeds Another in View of the Evidence of Two Samples. Biometrika (1933), 285--294."},{"key":"e_1_3_2_1_30_1","unstructured":"Chien-Yao Wang Alexey Bochkovskiy and Hong-Yuan Mark Liao. 2021. Scaled-YOLOv4: Scaling Cross Stage Partial Network. In CVPR. 13029--13038."},{"key":"e_1_3_2_1_31_1","unstructured":"Longyin Wen Dawei Du Zhaowei Cai Zhen Lei Ming-Ching Chang Honggang Qi Jongwoo Lim Ming-Hsuan Yang and Siwei Lyu. 2020. UA-DETRAC: A New Benchmark and Protocol for Multi-Object Detection and Tracking. In CVIU."},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3299869.3320230"},{"key":"e_1_3_2_1_33_1","unstructured":"Fisher Yu Haofeng Chen Xin Wang Wenqi Xian Yingying Chen Fangchen Liu Vashisht Madhavan and Trevor Darrell. 2020. BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning. (2020)."},{"key":"e_1_3_2_1_34_1","volume-title":"Panorama: A Data System for Unbounded Vocabulary Querying over Video. In PVLDB. 477--491.","author":"Zhang Yuhao","year":"2019","unstructured":"Yuhao Zhang and Arun Kumar. 2019. Panorama: A Data System for Unbounded Vocabulary Querying over Video. In PVLDB. 477--491."}],"event":{"name":"SIGMOD\/PODS '22: International Conference on Management of Data","location":"Philadelphia PA USA","acronym":"SIGMOD\/PODS '22","sponsor":["SIGMOD ACM Special Interest Group on Management of Data"]},"container-title":["Proceedings of the 2022 International Conference on Management of Data"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3514221.3517857","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3514221.3517857","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3514221.3517857","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:30:35Z","timestamp":1750188635000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3514221.3517857"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,10]]},"references-count":34,"alternative-id":["10.1145\/3514221.3517857","10.1145\/3514221"],"URL":"https:\/\/doi.org\/10.1145\/3514221.3517857","relation":{},"subject":[],"published":{"date-parts":[[2022,6,10]]},"assertion":[{"value":"2022-06-11","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}