2019
|
Monteiro, C. D. D.; Shipman, F. M.; III, S. Duggina; Gutierrez-Osuna, R. Tradeoffs in the Efficient Detection of Sign Language Content in Video Sharing Sites Journal Article In: ACM Transactions on Accessible Computing, vol. 12, no. 2, pp. 1-16, 2019. @article{caio2019asl,
title = {Tradeoffs in the Efficient Detection of Sign Language Content in Video Sharing Sites},
author = {C. D. D. Monteiro and F. M. Shipman and III, S. Duggina and R. Gutierrez-Osuna},
url = {https://dl.acm.org/doi/10.1145/3325863
https://psi.engr.tamu.edu/wp-content/uploads/2020/04/caio2019asl.pdf},
year = {2019},
date = {2019-06-01},
journal = {ACM Transactions on Accessible Computing},
volume = {12},
number = {2},
pages = {1-16},
keywords = {Computer vision, Speech},
pubstate = {published},
tppubtype = {article}
}
|
2017
|
Shipman, F; Duggina, S; Monteiro, C; Gutierrez-Osuna, R Speed-Accuracy Tradeoffs for Detecting Sign Language Content in Video Sharing Sites Proceedings Article In: Proceedings of ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2017), pp. 185-189, 2017. @inproceedings{shipman2017assets,
title = {Speed-Accuracy Tradeoffs for Detecting Sign Language Content in Video Sharing Sites},
author = {F Shipman and S Duggina and C Monteiro and R Gutierrez-Osuna},
url = {https://psi.engr.tamu.edu/wp-content/uploads/2018/01/shipman2017assets.pdf},
year = {2017},
date = {2017-11-21},
booktitle = {Proceedings of ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2017)},
pages = {185-189},
keywords = {Computer vision, Gestures, Speech},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Nguyen, K. N.; Liu, X.; Komogortsevz, O.; Gutierrez-Osuna, R.; Choe, Y. Explanation of the Perceptual Oblique Effect Based on the Fidelity of Oculomotor Control During Saccades Proceedings Article In: 2017 Joint IEEE International Conference on Development and Learning, pp. 15-20, 2017. @inproceedings{saccades-2017-khuong,
title = {Explanation of the Perceptual Oblique Effect Based on the Fidelity of Oculomotor Control During Saccades},
author = {K. N. Nguyen and X. Liu and O. Komogortsevz and R. Gutierrez-Osuna and Y. Choe},
url = {https://psi.engr.tamu.edu/wp-content/uploads/2019/05/08329781-1.pdf},
year = {2017},
date = {2017-09-18},
booktitle = {2017 Joint IEEE International Conference on Development and Learning},
pages = {15-20},
keywords = {Computer vision},
pubstate = {published},
tppubtype = {inproceedings}
}
|
2016
|
Monteiro, C; Mathew, C; Shipman, F; Gutierrez-Osuna, R Detecting and Identifying Sign Languages through Visual Features Proceedings Article In: 2016 IEEE International Symposium on Multimedia (ISM), 2016. @inproceedings{monteiro2016ism,
title = {Detecting and Identifying Sign Languages through Visual Features},
author = {C Monteiro and C Mathew and F Shipman and R Gutierrez-Osuna},
url = {https://psi.engr.tamu.edu/wp-content/uploads/2018/01/monteiro2016ism.pdf},
year = {2016},
date = {2016-12-11},
booktitle = {2016 IEEE International Symposium on Multimedia (ISM)},
keywords = {Computer vision, Gestures, Pattern recognition},
pubstate = {published},
tppubtype = {inproceedings}
}
|
2015
|
Shipman, F; Gutierrez-Osuna, R; Shipman, T; Monteiro, C; Karappa, V Towards a Distributed Digital Library for Sign Language Content Proceedings Article In: Proc. ACM/IEEE Joint Conference on Digital Libraries, 2015. @inproceedings{shipman2015jcdl,
title = {Towards a Distributed Digital Library for Sign Language Content},
author = {F Shipman and R Gutierrez-Osuna and T Shipman and C Monteiro and V Karappa},
url = {https://psi.engr.tamu.edu/wp-content/uploads/2018/01/shipman2015jcdl.pdf},
year = {2015},
date = {2015-04-02},
booktitle = {Proc. ACM/IEEE Joint Conference on Digital Libraries},
volume = {in press},
keywords = {Computer vision, Gestures, Pattern recognition},
pubstate = {published},
tppubtype = {inproceedings}
}
|
2014
|
Karappa, V; Monteiro, C; Shipman, F; Gutierrez-Osuna, R Detection of sign-language content in video through polar motion profiles Proceedings Article In: Proc. 39th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pp. 1299-1303, 2014. @inproceedings{virendraasl2014icassp,
title = {Detection of sign-language content in video through polar motion profiles},
author = {V Karappa and C Monteiro and F Shipman and R Gutierrez-Osuna},
url = {https://psi.engr.tamu.edu/wp-content/uploads/2018/01/virendraasl2014icassp.pdf},
year = {2014},
date = {2014-05-09},
booktitle = {Proc. 39th International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
pages = {1299-1303},
keywords = {Computer vision, Gestures},
pubstate = {published},
tppubtype = {inproceedings}
}
|
2013
|
Shipman, F; Gutierrez-Osuna, R; Monteiro, C Identifying Sign Language Videos in Video Sharing Sites Journal Article In: ACM Transactions on Accessible Computing, vol. in press, 2013. @article{Shipman2013,
title = {Identifying Sign Language Videos in Video Sharing Sites},
author = {F Shipman and R Gutierrez-Osuna and C Monteiro},
url = {https://psi.engr.tamu.edu/wp-content/uploads/2018/01/Shipman2013.pdf},
year = {2013},
date = {2013-11-04},
journal = {ACM Transactions on Accessible Computing},
volume = {in press},
keywords = {Computer vision, Gestures},
pubstate = {published},
tppubtype = {article}
}
|
Lee, J; Gutierrez-Osuna, R; Young, S SILK: Scale-space integrated Lucas-Kanade image registration for super-resolution from video Conference 38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2013. @conference{josephicassp2013,
title = {SILK: Scale-space integrated Lucas-Kanade image registration for super-resolution from video},
author = {J Lee and R Gutierrez-Osuna and S Young},
url = {https://psi.engr.tamu.edu/wp-content/uploads/2018/01/josephicassp2013.pdf},
year = {2013},
date = {2013-02-28},
booktitle = {38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
keywords = {Computer vision},
pubstate = {published},
tppubtype = {conference}
}
|
2012
|
Monteiro, C; Gutierrez-Osuna, R; Shipman, F Design and Evaluation of Classifier for Identifying Sign Language Videos in Video Sharing Sites Conference 13th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2012)., 2012. @conference{monteiro2012assets,
title = {Design and Evaluation of Classifier for Identifying Sign Language Videos in Video Sharing Sites},
author = {C Monteiro and R Gutierrez-Osuna and F Shipman},
url = {https://psi.engr.tamu.edu/wp-content/uploads/2018/01/monteiro2012assets.pdf},
year = {2012},
date = {2012-10-22},
booktitle = {13th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2012).},
abstract = {Video sharing sites provide an opportunity for the collection and use of sign language presentations about a wide range of topics. Currently, locating sign language videos (SL videos) in such sharing sites relies on the existence and accuracy of tags, titles or other metadata indicating the content is in sign language. In this paper, we describe the design and evaluation of a classifier for distinguishing between sign language videos and other videos. A test collection of SL videos and videos likely to be incorrectly recognized as SL videos (likely false positives) was created for evaluating alternative classifiers. Five video features thought to be potentially valuable for this task were developed based on common video analysis techniques. A comparison of the relative value of the five video features shows that a measure of the symmetry of movement relative to the face is the best feature for distinguishing sign language videos. Overall, an SVM classifier provided with all five features achieves 82% precision and 90% recall when tested on the challenging test collection. The performance would be considerably higher when applied to the more varied collections of large video sharing sites.},
keywords = {Computer vision, Gestures},
pubstate = {published},
tppubtype = {conference}
}
Video sharing sites provide an opportunity for the collection and use of sign language presentations about a wide range of topics. Currently, locating sign language videos (SL videos) in such sharing sites relies on the existence and accuracy of tags, titles or other metadata indicating the content is in sign language. In this paper, we describe the design and evaluation of a classifier for distinguishing between sign language videos and other videos. A test collection of SL videos and videos likely to be incorrectly recognized as SL videos (likely false positives) was created for evaluating alternative classifiers. Five video features thought to be potentially valuable for this task were developed based on common video analysis techniques. A comparison of the relative value of the five video features shows that a measure of the symmetry of movement relative to the face is the best feature for distinguishing sign language videos. Overall, an SVM classifier provided with all five features achieves 82% precision and 90% recall when tested on the challenging test collection. The performance would be considerably higher when applied to the more varied collections of large video sharing sites. |
2011
|
Lee, J; Young, S S; Gutierrez-Osuna, R An Iterative Image Registration Technique Using a Scale-Space Model Technical Report 2011. @techreport{lee2011iterative,
title = {An Iterative Image Registration Technique Using a Scale-Space Model},
author = {J Lee and S S Young and R Gutierrez-Osuna},
url = {https://psi.engr.tamu.edu/wp-content/uploads/2018/01/lee2011iterative.pdf},
year = {2011},
date = {2011-12-01},
abstract = {Registration between two images is a key problem in computer vision. Current methods tend to separate the scale estimation process from translation and rotation estimation. This is due to the fact that the scale parameter is inherently related to the image resolution. In this paper, we present an area-based image registration technique that can simultaneously estimate translation, rotation, and scale parameters and take into account differences in resolution between two images. We first develop a scale-space model that relates the entire reference image pixels to a single observed image pixel with a scale parameter. This model is then easily generalized to include x-y translation and rotation parameters. By embedding this scale-space model into a non-linear least squares method, we can iteratively estimate the four registration parameters (x-y shift, rotation, and scale) in a unified manner. We test the validity of the proposed method on both simulated and real image data.},
keywords = {Computer vision},
pubstate = {published},
tppubtype = {techreport}
}
Registration between two images is a key problem in computer vision. Current methods tend to separate the scale estimation process from translation and rotation estimation. This is due to the fact that the scale parameter is inherently related to the image resolution. In this paper, we present an area-based image registration technique that can simultaneously estimate translation, rotation, and scale parameters and take into account differences in resolution between two images. We first develop a scale-space model that relates the entire reference image pixels to a single observed image pixel with a scale parameter. This model is then easily generalized to include x-y translation and rotation parameters. By embedding this scale-space model into a non-linear least squares method, we can iteratively estimate the four registration parameters (x-y shift, rotation, and scale) in a unified manner. We test the validity of the proposed method on both simulated and real image data. |