Publications

@inproceedings{2016-Bettadapura-LCCGBH,

title = {Leveraging Contextual Cues for Generating Basketball Highlights},

author = {Vinay Bettadapura and Caroline Pantofaru and Irfan Essa},

url = {https://dl.acm.org/doi/10.1145/2964284.2964286

http://www.vbettadapura.com/highlights/basketball/index.htm},

doi = {10.1145/2964284.2964286},

year  = {2016},

date = {2016-10-01},

urldate = {2016-10-01},

booktitle = {ACM International Conference on Multimedia (ACM-MM)},

organization = {ACM},

abstract = {The massive growth of sports videos has resulted in a need for automatic generation of sports highlights that are comparable in quality to the hand-edited highlights produced by broadcasters such as ESPN. Unlike previous works that mostly use audio-visual cues derived from the video, we propose an approach that additionally leverages contextual cues derived from the environment that the game is being played in. The contextual cues provide information about the excitement levels in the game, which can be ranked and selected to automatically produce high-quality basketball highlights. We introduce a new dataset of 25 NCAA games along with their play-by-play stats and the ground-truth excitement data for each basket. We explore the informativeness of five different cues derived from the video and from the environment through user studies. Our experiments show that for our study participants, the highlights produced by our system are comparable to the ones produced by ESPN for the same games.},

keywords = {ACM, ACMMM, activity recognition, computational video, computer vision, sports visualization, video summarization},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{2006-Kim-IMGVN,

title = {Interactive Mosaic Generation for Video Navigation},

author = {Kihwan Kim and Irfan Essa and Gregory Abowd },

url = {https://doi.org/10.1145/1180639.1180776},

doi = {10.1145/1180639.1180776},

year  = {2006},

date = {2006-10-01},

urldate = {2006-10-01},

booktitle = {ACM International Conference on Multimedia (ACM-MM)},

address = {Santa Barbara,CA,USA},

abstract = {Navigation through large multimedia collections that include videos and images still remains cumbersome. In this paper, we introduce a novel method to visualize and navigate through the collection by creating a mosaic image that visually represents the compilation. This image is generated by a labeling-based layout algorithm using various sizes of sample tile images from the collection. Each tile represents both the photographs and video files representing scenes selected by matching algorithms. This generated mosaic image provides a new way for thematic video and visually summarizes the videos. Users can generate these mosaics with some predefined themes and layouts, or base it on the results of their queries. Our approach supports automatic generation of these layouts by using meta-information such as color, time-line and existence of faces or manually generated annotated information from existing systems (e.g., the Family Video Archive).},

keywords = {ACMMM, computational video, multimedia},

pubstate = {published},

tppubtype = {inproceedings}

}