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31 results on '"Davila, Kenny"'

1. Synthetic Data Generation for Semantic Segmentation of Lecture Videos

Author

Davila, Kenny, Xu, Fei, Molina, James, Setlur, Srirangaraj, Govindaraju, Venu, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Porwal, Utkarsh, editor, Fornés, Alicia, editor, and Shafait, Faisal, editor

Published
2022
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2. Skeleton-Based Methods for Speaker Action Classification on Lecture Videos

Author

Xu, Fei, Davila, Kenny, Setlur, Srirangaraj, Govindaraju, Venu, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Del Bimbo, Alberto, editor, Cucchiara, Rita, editor, Sclaroff, Stan, editor, Farinella, Giovanni Maria, editor, Mei, Tao, editor, Bertini, Marco, editor, Escalante, Hugo Jair, editor, and Vezzani, Roberto, editor

Published
2021
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3. ICPR 2020 - Competition on Harvesting Raw Tables from Infographics

Author

Davila, Kenny, Tensmeyer, Chris, Shekhar, Sumit, Singh, Hrituraj, Setlur, Srirangaraj, Govindaraju, Venu, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Del Bimbo, Alberto, editor, Cucchiara, Rita, editor, Sclaroff, Stan, editor, Farinella, Giovanni Maria, editor, Mei, Tao, editor, Bertini, Marco, editor, Escalante, Hugo Jair, editor, and Vezzani, Roberto, editor

Published
2021
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5. The Tangent Search Engine: Improved Similarity Metrics and Scalability for Math Formula Search

Author

Zanibbi, Richard, Davila, Kenny, Kane, Andrew, and Tompa, Frank

Subjects
Computer Science - Information Retrieval, H.2.4, H.3.3, H.3.4
Abstract

With the ever-increasing quantity and variety of data worldwide, the Web has become a rich repository of mathematical formulae. This necessitates the creation of robust and scalable systems for Mathematical Information Retrieval, where users search for mathematical information using individual formulae (query-by-expression) or a combination of keywords and formulae. Often, the pages that best satisfy users' information needs contain expressions that only approximately match the query formulae. For users trying to locate or re-find a specific expression, browse for similar formulae, or who are mathematical non-experts, the similarity of formulae depends more on the relative positions of symbols than on deep mathematical semantics. We propose the Maximum Subtree Similarity (MSS) metric for query-by-expression that produces intuitive rankings of formulae based on their appearance, as represented by the types and relative positions of symbols. Because it is too expensive to apply the metric against all formulae in large collections, we first retrieve expressions using an inverted index over tuples that encode relationships between pairs of symbols, ranking hits using the Dice coefficient. The top-k formulae are then re-ranked using MSS. Our approach obtains state-of-the-art performance on the NTCIR-11 Wikipedia formula retrieval benchmark and is efficient in terms of both index space and overall retrieval time. Retrieval systems for other graphical forms, including chemical diagrams, flowcharts, figures, and tables, may also benefit from adopting our approach., Comment: 10 pages

Published
2015

6. Tangent-V: Math Formula Image Search Using Line-of-Sight Graphs

Author

Davila, Kenny, Joshi, Ritvik, Setlur, Srirangaraj, Govindaraju, Venu, Zanibbi, Richard, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Azzopardi, Leif, editor, Stein, Benno, editor, Fuhr, Norbert, editor, Mayr, Philipp, editor, Hauff, Claudia, editor, and Hiemstra, Djoerd, editor

Published
2019
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10. Generalized framework for summarization of fixed-camera lecture videos by detecting and binarizing handwritten content

Author

Urala Kota, Bhargava, Davila, Kenny, Stone, Alexander, Setlur, Srirangaraj, and Govindaraju, Venu

Abstract

We propose a framework to extract and binarize handwritten content in lecture videos. The extracted content could potentially be used to index video collections powering content-based search and navigation within lecture videos helping students and educators across the world. A deep learning pipeline is used to detect handwritten text, formulae and sketches and then binarize the extracted content. We exploit the spatio-temporal structure of our binarized detections to compute associativity information of content across all video frames. This information is later used to segment the video. Experiments are conducted to compare the performance of key components of our framework in isolation, as well as the impact on overall performance, with respect to existing methods. We evaluate our framework on the publicly available AccessMath lecture video dataset obtaining an f-measure of $$94.32\%$$94.32%for binary connected components. Code for the framework (including trained weights) and summarization will be released.

Published
2024
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