Computational Imaging & VisAnalysis

#345: E. Asante, D. Hummel, S. Gurung, Y. Kassim, N. Al-Shakarji, K. Palaniappan, V. Sittaramane, and A. Chandrasekhar

Defective neuronal positioning correlates with aberrant motor circuit function in zebrafish

Frontiers in Neural Circuits, Volume 15, 2021

jaw movement, food intake, behavior, neuronal migration, axon guidance, zebrafish, neural circuits, facial branchiomotor neuron, fusion, biomedical

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar

@article{Zebafish2021:FrontiersJornal,
  author = "E. Asante and D. Hummel and S. Gurung and Y. Kassim and N. Al-Shakarji and K. Palaniappan and V. Sittaramane and A. Chandrasekhar",
  title = "Defective neuronal positioning correlates with aberrant motor circuit function in zebrafish",
  year = 2021,
  journal = "Frontiers in Neural Circuits",
  volume = 15,
  keywords = "jaw movement, food intake, behavior, neuronal migration, axon guidance, zebrafish, neural circuits, facial branchiomotor neuron, fusion, biomedical",
  doi = "10.3389/fncir.2021.690475",
  url = "https://www.frontiersin.org/article/10.3389/fncir.2021.690475"
}

E. Asante, D. Hummel, S. Gurung, Y. Kassim, N. Al-Shakarji, K. Palaniappan, V. Sittaramane, and A. Chandrasekhar. Defective neuronal positioning correlates with aberrant motor circuit function in zebrafish. Frontiers in Neural Circuits, volume 15, 2021.

#337: N. Al-Shakarji, K. Gao, F. Bunyak, H. Aliakbarpour, E. Blasch, P. Narayaran, G. Seetharaman, and K. Palaniappan

Impact of georegistration accuracy on wide area motion imagery object detection and tracking

IEEE International Conference on Information Fusion (FUSION), pgs. 1-8, 2021

deep learning, fusion, wami, object detection, multi-object tracking, dod

Abstract, Bibtex, PlainText, PDF, URL, Google Scholar

@inproceedings{Noor2021:Fusion_ImpactGeoReg,
  author = "N. Al-Shakarji and K. Gao and F. Bunyak and H. Aliakbarpour and E. Blasch and P. Narayaran and G. Seetharaman and K. Palaniappan",
  title = "Impact of georegistration accuracy on wide area motion imagery object detection and tracking",
  year = 2021,
  booktitle = "IEEE International Conference on Information Fusion (FUSION)",
  pages = "1-8",
  keywords = "deep learning, fusion, wami, object detection, multi-object tracking, dod",
  url = "https://ieeexplore.ieee.org/document/9626982"
}

N. Al-Shakarji, K. Gao, F. Bunyak, H. Aliakbarpour, E. Blasch, P. Narayaran, G. Seetharaman, and K. Palaniappan. Impact of georegistration accuracy on wide area motion imagery object detection and tracking. IEEE International Conference on Information Fusion (FUSION), pages 1-8, 2021.

#274: A. Bouix, N. Al-Shakarji, K. Gao, F. Bunyak, A. Chazot, A. Hafiane, and K. Palaniappan

Robust target tracking using adaptive color feature and likelihood fusion

International Society for Optics and Photonics, Volume 10645, pgs. 106450L, 2018

visual object tracking, staple, correlation filter, color name, fusion

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar

@inproceedings{Bouix2018:AIPR_iSTAPLE,
  author = "A. Bouix and N. Al-Shakarji and K. Gao and F. Bunyak and A. Chazot and A. Hafiane and K. Palaniappan",
  title = "Robust target tracking using adaptive color feature and likelihood fusion",
  year = 2018,
  journal = "International Society for Optics and Photonics",
  booktitle = "Geospatial Informatics, Motion Imagery, and Network Analytics VIII",
  volume = 10645,
  pages = "106450L",
  month = "Apr",
  keywords = "visual object tracking, staple, correlation filter, color name, fusion",
  doi = "10.1117/12.2309807",
  url = "https://www.spiedigitallibrary.org/conference-proceedings-of-spie/10645/106450L/Robust-target-tracking-using-adaptive-color-feature-and-likelihood-fusion/10.1117/12.2309807.full"
}

A. Bouix, N. Al-Shakarji, K. Gao, F. Bunyak, A. Chazot, A. Hafiane, and K. Palaniappan. Robust target tracking using adaptive color feature and likelihood fusion. International Society for Optics and Photonics, Geospatial Informatics, Motion Imagery, and Network Analytics VIII, volume 10645, pages 106450L, April 2018.

#172: H. Aliakbarpour, K. Palaniappan, and J. Dias

Geometric exploration of virtual planes in a fusion-based 3D registration framework

Proc. SPIE Conf. Geospatial InfoFusion III (Defense, Security and Sensing: Sensor Data and Information Exploitation), Volume 8747, pgs. 87470C, 2013

3d reconstruction, wami, registration, fusion, fmv, dod

Abstract, Bibtex, PlainText, PDF, DOI, Google Scholar

@inproceedings{Hadi:virtual-planes_SPIE-2013,
  author = "H. Aliakbarpour and K. Palaniappan and J. Dias",
  title = "Geometric exploration of virtual planes in a fusion-based 3D registration framework",
  year = 2013,
  booktitle = "Proc. SPIE Conf. Geospatial InfoFusion III (Defense, Security and Sensing: Sensor Data and Information Exploitation)",
  volume = 8747,
  pages = "87470C",
  keywords = "3d reconstruction, wami, registration, fusion, fmv, dod",
  doi = "10.1117/12.2015933"
}

H. Aliakbarpour, K. Palaniappan, and J. Dias. Geometric exploration of virtual planes in a fusion-based 3D registration framework. Proc. SPIE Conf. Geospatial InfoFusion III (Defense, Security and Sensing: Sensor Data and Information Exploitation), volume 8747, pages 87470C, 2013.

#140: E. Blasch, G. Seetharaman, K. Palaniappan, H. Ling, and G. Chen

Wide-Area Motion Imagery (WAMI) exploitation tools for enhanced situational awareness

Proc. IEEE Applied Imagery Pattern Recognition Workshop, 2012

wami, visual events, fusion, data mining, fmv, dod

Abstract, Bibtex, PlainText, PDF, URL, Google Scholar

@inproceedings{Blasch:wami-tools-2012,
  author = "E. Blasch and G. Seetharaman and K. Palaniappan and H. Ling and G. Chen",
  title = "Wide-Area Motion Imagery (WAMI) exploitation tools for enhanced situational awareness",
  year = 2012,
  booktitle = "Proc. IEEE Applied Imagery Pattern Recognition Workshop",
  keywords = "wami, visual events, fusion, data mining, fmv, dod",
  url = "http://www.dabi.temple.edu/~hbling/publication/AIPR12_WAMI_for_E2ATv4_BW.pdf"
}

E. Blasch, G. Seetharaman, K. Palaniappan, H. Ling, and G. Chen. Wide-Area Motion Imagery (WAMI) exploitation tools for enhanced situational awareness. Proc. IEEE Applied Imagery Pattern Recognition Workshop, 2012.

#148: A. Camargo, Q. He, and K. Palaniappan

Performance evaluation of optimization methods for super-resolution mosaicking on UAS surveillance videos

Proc. SPIE Infrared Imaging Systems: Design, Analysis, Modeling and Testing XXIII, Volume 8355, 2012

image enhancement, wami, visual events, fusion, fmv, dod

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar

@inproceedings{Camargo:super-resolution_SPIE-2012,
  author = "A. Camargo and Q. He and K. Palaniappan",
  title = "Performance evaluation of optimization methods for super-resolution mosaicking on UAS surveillance videos",
  year = 2012,
  booktitle = "Proc. SPIE Infrared Imaging Systems: Design, Analysis, Modeling and Testing XXIII",
  volume = 8355,
  keywords = "image enhancement, wami, visual events, fusion, fmv, dod",
  doi = "10.1117/12.919641",
  url = "http://proceedings.spiedigitallibrary.org/proceeding.aspx?articleid=1385560"
}

A. Camargo, Q. He, and K. Palaniappan. Performance evaluation of optimization methods for super-resolution mosaicking on UAS surveillance videos. Proc. SPIE Infrared Imaging Systems: Design, Analysis, Modeling and Testing XXIII, volume 8355, 2012.

#154: I. Ersoy, K. Palaniappan, G. Seetharaman, and R. Rao

Interactive tracking for persistent wide-area surveillance

Proc. SPIE Conf. Geospatial InfoFusion II (Defense, Security and Sensing: Sensor Data and Information Exploitation), Volume 8396, 2012

wami, tracking, fmv, features, motion, fusion, dod

Abstract, Bibtex, PlainText, PDF, Google Scholar

@inproceedings{Ersoy:tracking_SPIE-2012,
  author = "I. Ersoy and K. Palaniappan and G. Seetharaman and R. Rao",
  title = "Interactive tracking for persistent wide-area surveillance",
  year = 2012,
  booktitle = "Proc. SPIE Conf. Geospatial InfoFusion II (Defense, Security and Sensing: Sensor Data and Information Exploitation)",
  volume = 8396,
  keywords = "wami, tracking, fmv, features, motion, fusion, dod"
}

I. Ersoy, K. Palaniappan, G. Seetharaman, and R. Rao. Interactive tracking for persistent wide-area surveillance. Proc. SPIE Conf. Geospatial InfoFusion II (Defense, Security and Sensing: Sensor Data and Information Exploitation), volume 8396, 2012.

#159: S. Candemir, K. Palaniappan, F. Bunyak, and G. Seetharaman

Feature fusion using ranking for object tracking in aerial imagery

Proc. SPIE Conf. Geospatial InfoFusion II (Defense, Security and Sensing: Sensor Data and Information Exploitation), Volume 8396, 2012

wami, tracking, fmv, features, motion, fusion, dod

Abstract, Bibtex, PlainText, PDF, DOI, Google Scholar

Aerial wide-area monitoring and tracking using multi-camera arrays poses unique challenges compared to stan- dard full motion video analysis due to low frame rate sampling, accurate registration due to platform motion, low resolution targets, limited image contrast, static and dynamic parallax occlusions.1–3 We have developed a low frame rate tracking system that fuses a rich set of intensity, texture and shape features, which enables adaptation of the tracker to dynamic environment changes and target appearance variabilities. However, improper fusion and overweighting of low quality features can adversely affect target localization and reduce tracking performance. Moreover, the large computational cost associated with extracting a large number of image-based feature sets will influence tradeoffs for real-time and on-board tracking. This paper presents a framework for dynamic online ranking-based feature evaluation and fusion in aerial wide-area tracking. We describe a set of efficient descriptors suitable for small sized targets in aerial video based on intensity, texture, and shape feature representations or views. Feature ranking is then used as a selection procedure where target-background discrimination power for each (raw) feature view is scored using a two-class variance ratio approach. A subset of the k-best discriminative features are selected for further processing and fusion. The target match probability or likelihood maps for each of the k features are estimated by comparing target descriptors within a search region using a sliding win- dow approach. The resulting k likelihood maps are fused for target localization using the normalized variance ratio weights. We quantitatively measure the performance of the proposed system using ground-truth tracks within the framework of our tracking evaluation test-bed that incorporates various performance metrics. The proposed feature ranking and fusion approach increases localization accuracy by reducing multimodal effects due to low quality features or background clutter. Adaptive feature ranking increases the robustness of the tracker in dynamically changing environments especially when the object appearance is changing.

@inproceedings{Sema:Feature-ranking_SPIE-2012,
  author = "S. Candemir and K. Palaniappan and F. Bunyak and G. Seetharaman",
  title = "Feature fusion using ranking for object tracking in aerial imagery",
  year = 2012,
  booktitle = "Proc. SPIE Conf. Geospatial InfoFusion II (Defense, Security and Sensing: Sensor Data and Information Exploitation)",
  volume = 8396,
  keywords = "wami, tracking, fmv, features, motion, fusion, dod",
  doi = "10.1117/12.920529"
}

S. Candemir, K. Palaniappan, F. Bunyak, and G. Seetharaman. Feature fusion using ranking for object tracking in aerial imagery. Proc. SPIE Conf. Geospatial InfoFusion II (Defense, Security and Sensing: Sensor Data and Information Exploitation), volume 8396, 2012.

#153: J. Peng, K. Palaniappan, S. Candemir, and G. Seetharaman

Kullback-Leibler divergence-based data fusion for target tracking

Int. Conf. Pattern Recognition, 2012

wami, tracking, fmv, features, motion, fusion, data mining, machine learning, dod

Abstract, Bibtex, PlainText, PDF, URL, Google Scholar

@inproceedings{JPeng:ICPR-2012,
  author = "J. Peng and K. Palaniappan and S. Candemir and G. Seetharaman",
  title = "Kullback-Leibler divergence-based data fusion for target tracking",
  year = 2012,
  booktitle = "Int. Conf. Pattern Recognition",
  keywords = "wami, tracking, fmv, features, motion, fusion, data mining, machine learning, dod",
  url = "http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=6460914"
}

J. Peng, K. Palaniappan, S. Candemir, and G. Seetharaman. Kullback-Leibler divergence-based data fusion for target tracking. Int. Conf. Pattern Recognition, 2012.

#147: R. Pelapur, S. Candemir, F. Bunyak, M. Poostchi, G. Seetharaman, and K. Palaniappan

Persistent target tracking using likelihood fusion in wide-area and full motion video sequences

15th Int. Conf. Information Fusion, pgs. 2420--2427, 2012

wami, tracking, fmv, motion, features, fusion, dod

Abstract, Bibtex, PlainText, PDF, URL, Google Scholar

@inproceedings{Rengarajan:LOFTSystem_FUSION2012,
  author = "R. Pelapur and S. Candemir and F. Bunyak and M. Poostchi and G. Seetharaman and K. Palaniappan",
  title = "Persistent target tracking using likelihood fusion in wide-area and full motion video sequences",
  year = 2012,
  booktitle = "15th Int. Conf. Information Fusion",
  pages = "2420--2427",
  keywords = "wami, tracking, fmv, motion, features, fusion, dod",
  url = "http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6290597"
}

R. Pelapur, S. Candemir, F. Bunyak, M. Poostchi, G. Seetharaman, and K. Palaniappan. Persistent target tracking using likelihood fusion in wide-area and full motion video sequences. 15th Int. Conf. Information Fusion, pages 2420--2427, 2012.

#151: V. B. S. Prasath, K. Palaniappan, and G. Seetharaman

Multichannel texture image segmentation using local feature fitting based variational active contours

8th Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP), 2012

active contours, color, texture, segmentation, features, fusion

Abstract, Bibtex, PlainText, PDF, DOI, Google Scholar

@inproceedings{Surya:ICVGIP-2012-local-texture,
  author = "V. B. S. Prasath and K. Palaniappan and G. Seetharaman",
  title = "Multichannel texture image segmentation using local feature fitting based variational active contours",
  year = 2012,
  booktitle = "8th Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP)",
  keywords = "active contours, color, texture, segmentation, features, fusion",
  doi = "10.1145/2425333.2425411"
}

V. B. S. Prasath, K. Palaniappan, and G. Seetharaman. Multichannel texture image segmentation using local feature fitting based variational active contours. 8th Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP), 2012.

#158: S. Candemir, K. Palaniappan, F. Bunyak, G. Seetharaman, and R. Rao

Feature prominence-based weighting scheme for video tracking

8th Indian Conference on Computer Vision, Graphics and Image Processing, 2012

wami, tracking, fmv, motion, features, fusion, dod

Abstract, Bibtex, PlainText, PDF, DOI, Google Scholar

@inproceedings{Sema:ICVGIP-2012-feature-prom,
  author = "S. Candemir and K. Palaniappan and F. Bunyak and G. Seetharaman and R. Rao",
  title = "Feature prominence-based weighting scheme for video tracking",
  year = 2012,
  booktitle = "8th Indian Conference on Computer Vision, Graphics and Image Processing",
  keywords = "wami, tracking, fmv, motion, features, fusion, dod",
  doi = "10.1145/2425333.2425358"
}

S. Candemir, K. Palaniappan, F. Bunyak, G. Seetharaman, and R. Rao. Feature prominence-based weighting scheme for video tracking. 8th Indian Conference on Computer Vision, Graphics and Image Processing, 2012.

#120: K. Palaniappan, R. Rao, and G. Seetharaman

Wide-area persistent airborne video: Architecture and challenges

Distributed Video Sensor Networks: Research Challenges and Future Directions, Springer, pgs. 349--371, 2011

wami, tracking, fmv, features, motion, fusion, dod

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar

@incollection{Pal:DVSNbook-2011,
  author = "K. Palaniappan and R. Rao and G. Seetharaman",
  title = "Wide-area persistent airborne video: Architecture and challenges",
  year = 2011,
  booktitle = "Distributed Video Sensor Networks: Research Challenges and Future Directions",
  publisher = "Springer",
  pages = "349--371",
  keywords = "wami, tracking, fmv, features, motion, fusion, dod",
  doi = "10.1007/978-0-85729-127-1_24",
  url = "http://link.springer.com/chapter/10.1007/978-0-85729-127-1_24"
}

K. Palaniappan, R. Rao, and G. Seetharaman. Wide-area persistent airborne video: Architecture and challenges. Distributed Video Sensor Networks: Research Challenges and Future Directions, Springer, pages 349--371, 2011.

#136: E. Blasch, P. Deignan, S. Dockstader, M. Pellechia, K. Palaniappan, and G. Seetharaman

Contemporary concerns in Geographical/Geospatial Information Systems (GIS) processing

Proc. IEEE National Aerospace and Electronics Conference (NAECON), pgs. 183--190, 2011

wami, visual events, fusion, data mining, gis, dod

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar

@inproceedings{Blasch:GIS-NAECON-2011,
  author = "E. Blasch and P. Deignan and S. Dockstader and M. Pellechia and K. Palaniappan and G. Seetharaman",
  title = "Contemporary concerns in Geographical/Geospatial Information Systems (GIS) processing",
  year = 2011,
  booktitle = "Proc. IEEE National Aerospace and Electronics Conference (NAECON)",
  pages = "183--190",
  keywords = "wami, visual events, fusion, data mining, gis, dod",
  doi = "10.1109/NAECON.2011.6183099",
  url = "http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6183099"
}

E. Blasch, P. Deignan, S. Dockstader, M. Pellechia, K. Palaniappan, and G. Seetharaman. Contemporary concerns in Geographical/Geospatial Information Systems (GIS) processing. Proc. IEEE National Aerospace and Electronics Conference (NAECON), pages 183--190, 2011.

#114: K. Palaniappan, F. Bunyak, P. Kumar, I. Ersoy, S. Jaeger, K. Ganguli, A. Haridas, J. Fraser, R. Rao, and G. Seetharaman

Efficient feature extraction and likelihood fusion for vehicle tracking in low frame rate airborne video

13th Int. Conf. Information Fusion, 2010

wami, tracking, fmv, motion, features, fusion, dod

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar

@inproceedings{Pal:Fusion-2010,
  author = "K. Palaniappan and F. Bunyak and P. Kumar and I. Ersoy and S. Jaeger and K. Ganguli and A. Haridas and J. Fraser and R. Rao and G. Seetharaman",
  title = "Efficient feature extraction and likelihood fusion for vehicle tracking in low frame rate airborne video",
  year = 2010,
  booktitle = "13th Int. Conf. Information Fusion",
  keywords = "wami, tracking, fmv, motion, features, fusion, dod",
  doi = "10.1109/ICIF.2010.5711891",
  url = "http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5711891"
}

K. Palaniappan, F. Bunyak, P. Kumar, I. Ersoy, S. Jaeger, K. Ganguli, A. Haridas, J. Fraser, R. Rao, and G. Seetharaman. Efficient feature extraction and likelihood fusion for vehicle tracking in low frame rate airborne video. 13th Int. Conf. Information Fusion, 2010.

#88: M. H. Kolekar, K. Palaniappan, S. Sengupta, and G. Seetharaman

Semantic concept mining based on hierarchical event detection for soccer video indexing

J. Multimedia, Volume 4, pgs. 298--312, 2009

fmv, motion, features, fusion, visual events, data mining, cbir

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar

@article{Kolekar:JMM-2009,
  author = "M. H. Kolekar and K. Palaniappan and S. Sengupta and G. Seetharaman",
  title = "Semantic concept mining based on hierarchical event detection for soccer video indexing",
  year = 2009,
  journal = "J. Multimedia",
  volume = 4,
  number = 5,
  pages = "298--312",
  month = "Oct",
  keywords = "fmv, motion, features, fusion, visual events, data mining, cbir",
  doi = "10.4304/jmm.4.5.298-312",
  url = "http://ojs.academypublisher.com/index.php/jmm/article/view/2255"
}

M. H. Kolekar, K. Palaniappan, S. Sengupta, and G. Seetharaman. Semantic concept mining based on hierarchical event detection for soccer video indexing. J. Multimedia, volume 4, issue 5, pages 298--312, October 2009.

#96: K. Palaniappan, I. Ersoy, A. Hafiane, and G. Seetharaman

Moving object detection in UAV-video using flux tensors

IEEE Int. Geoscience and Remote Sensing Symposium, 2009

wami, tracking, fmv, registration, motion, fusion, dod

Bibtex, PlainText, Google Scholar

@inproceedings{Hafiane:IGARSS-2009,
  author = "K. Palaniappan and I. Ersoy and A. Hafiane and G. Seetharaman",
  title = "Moving object detection in UAV-video using flux tensors",
  year = 2009,
  booktitle = "IEEE Int. Geoscience and Remote Sensing Symposium",
  keywords = "wami, tracking, fmv, registration, motion, fusion, dod"
}

#100: M. H. Kolekar, K. Palaniappan, S. Sengupta, and G. Seetharaman

Event detection and semantic identification using Bayesian belief networks

IEEE Int. Conf. Computer Vision Workshops, pgs. 554--561, 2009

fmv, motion, features, fusion, visual events, data mining, cbir

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar

@inproceedings{Kolekar:ICCVW-2009,
  author = "M. H. Kolekar and K. Palaniappan and S. Sengupta and G. Seetharaman",
  title = "Event detection and semantic identification using Bayesian belief networks",
  year = 2009,
  booktitle = "IEEE Int. Conf. Computer Vision Workshops",
  pages = "554--561",
  keywords = "fmv, motion, features, fusion, visual events, data mining, cbir",
  doi = "10.1109/ICCVW.2009.5457652",
  url = "http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5457652"
}

M. H. Kolekar, K. Palaniappan, S. Sengupta, and G. Seetharaman. Event detection and semantic identification using Bayesian belief networks. IEEE Int. Conf. Computer Vision Workshops, pages 554--561, 2009.

#86: M. H. Kolekar and K. Palaniappan

A hierarchical framework for semantic scene classification in soccer sports video

IEEE Region Ten (TENCON) Int. Conference, pgs. Online, 2008

fmv, features, fusion, visual events, data mining, cbir

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar

@inproceedings{Kolekar:TENCON-2008,
  author = "M. H. Kolekar and K. Palaniappan",
  title = "A hierarchical framework for semantic scene classification in soccer sports video",
  year = 2008,
  booktitle = "IEEE Region Ten (TENCON) Int. Conference",
  pages = "Online",
  keywords = "fmv, features, fusion, visual events, data mining, cbir",
  doi = "10.1109/TENCON.2008.4766547",
  url = "http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=4766547"
}

M. H. Kolekar and K. Palaniappan. A hierarchical framework for semantic scene classification in soccer sports video. IEEE Region Ten (TENCON) Int. Conference, pages Online, 2008.

#72: M. H. Kolekar, K. Palaniappan, and S. Sengupta

Semantic event detection and classification in cricket video sequence

IEEE Indian Conference on Computer Vision, Graphics and Image Processing, pgs. 382--389, 2008

fmv, features, fusion, visual events, data mining, cbir

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar

@inproceedings{Kolekar:CVGIP-2008,
  author = "M. H. Kolekar and K. Palaniappan and S. Sengupta",
  title = "Semantic event detection and classification in cricket video sequence",
  year = 2008,
  booktitle = "IEEE Indian Conference on Computer Vision, Graphics and Image Processing",
  pages = "382--389",
  keywords = "fmv, features, fusion, visual events, data mining, cbir",
  doi = "10.1109/ICVGIP.2008.102",
  url = "http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=4756096"
}

M. H. Kolekar, K. Palaniappan, and S. Sengupta. Semantic event detection and classification in cricket video sequence. IEEE Indian Conference on Computer Vision, Graphics and Image Processing, pages 382--389, 2008.

#85: M. H. Kolekar, K. Palaniappan, and S. Sengupta

A novel framework for semantic annotation of soccer sports video sequences

Proc. 5th IEEE European Conference on Visual Media Production, pgs. 1-9, 2008

fmv, features, fusion, visual events, data mining, cbir

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar

@inproceedings{Kolekar:CVMP-2008,
  author = "M. H. Kolekar and K. Palaniappan and S. Sengupta",
  title = "A novel framework for semantic annotation of soccer sports video sequences",
  year = 2008,
  booktitle = "Proc. 5th IEEE European Conference on Visual Media Production",
  pages = "1-9",
  keywords = "fmv, features, fusion, visual events, data mining, cbir",
  doi = "10.1049/cp:20081081",
  url = "http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=4778745"
}

M. H. Kolekar, K. Palaniappan, and S. Sengupta. A novel framework for semantic annotation of soccer sports video sequences. Proc. 5th IEEE European Conference on Visual Media Production, pages 1-9, 2008.

#71: A. Hafiane, K. Palaniappan, and G. Seetharaman

UAV-Video registration using block-based features

IEEE Int. Geoscience and Remote Sensing Symposium, Volume II, pgs. 1104-1107, 2008

wami, tracking, fmv, registration, motion, fusion, dod

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar

@inproceedings{Hafiane:IGARSS-2008,
  author = "A. Hafiane and K. Palaniappan and G. Seetharaman",
  title = "UAV-Video registration using block-based features",
  year = 2008,
  booktitle = "IEEE Int. Geoscience and Remote Sensing Symposium",
  volume = II,
  pages = "1104-1107",
  keywords = "wami, tracking, fmv, registration, motion, fusion, dod",
  doi = "10.1109/IGARSS.2008.4779192",
  url = "http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=4779192"
}

A. Hafiane, K. Palaniappan, and G. Seetharaman. UAV-Video registration using block-based features. IEEE Int. Geoscience and Remote Sensing Symposium, volume II, pages 1104-1107, 2008.

#69: F. Bunyak, K. Palaniappan, S. K. Nath, and G. Seetharaman

Flux tensor constrained geodesic active contours with sensor fusion for persistent object tracking

J. Multimedia, Volume 2, pgs. 20--33, 2007

motion, fusion, tracking, active contours, visual events, features

Abstract, Bibtex, PlainText, PDF, URL, Google Scholar

@article{Bunyak:JMM-2007,
  author = "F. Bunyak and K. Palaniappan and S. K. Nath and G. Seetharaman",
  title = "Flux tensor constrained geodesic active contours with sensor fusion for persistent object tracking",
  year = 2007,
  journal = "J. Multimedia",
  volume = 2,
  number = 4,
  pages = "20--33",
  month = "Aug",
  keywords = "motion, fusion, tracking, active contours, visual events, features",
  url = "http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2605095/"
}

F. Bunyak, K. Palaniappan, S. K. Nath, and G. Seetharaman. Flux tensor constrained geodesic active contours with sensor fusion for persistent object tracking. J. Multimedia, volume 2, issue 4, pages 20--33, August 2007.

#68: F. Bunyak, K. Palaniappan, S. K. Nath, and G. Seetharaman

Geodesic active contour based fusion of visible and infrared video for persistent object tracking

8th IEEE Workshop Applications of Computer Vision (WACV 2007), pgs. Online, 2007

motion, fusion, tracking, active contours, visual events, features

Abstract, Bibtex, PlainText, PDF, DOI, Google Scholar

@inproceedings{Bunyak:WACV-2007,
  author = "F. Bunyak and K. Palaniappan and S. K. Nath and G. Seetharaman",
  title = "Geodesic active contour based fusion of visible and infrared video for persistent object tracking",
  year = 2007,
  booktitle = "8th IEEE Workshop Applications of Computer Vision (WACV 2007)",
  pages = "Online",
  keywords = "motion, fusion, tracking, active contours, visual events, features",
  doi = "10.1109/WACV.2007.26"
}

F. Bunyak, K. Palaniappan, S. K. Nath, and G. Seetharaman. Geodesic active contour based fusion of visible and infrared video for persistent object tracking. 8th IEEE Workshop Applications of Computer Vision (WACV 2007), pages Online, 2007.

#66: K. Palaniappan, I. Ersoy, and S. K. Nath

Moving object segmentation using the flux tensor for biological video microscopy

Lecture Notes in Computer Science (PCM), Volume 4810, pgs. 483-493, 2007

motion, fusion, tracking, active contours, features

Abstract, Bibtex, PlainText, URL, DOI, Google Scholar

@article{Palani:PCM-2007,
  author = "K. Palaniappan and I. Ersoy and S. K. Nath",
  title = "Moving object segmentation using the flux tensor for biological video microscopy",
  year = 2007,
  journal = "Lecture Notes in Computer Science (PCM)",
  volume = 4810,
  pages = "483-493",
  keywords = "motion, fusion, tracking, active contours, features",
  doi = "10.1007/978-3-540-77255-2_63",
  url = "http://link.springer.com/chapter/10.1007%2F978-3-540-77255-2_63"
}

K. Palaniappan, I. Ersoy, and S. K. Nath. Moving object segmentation using the flux tensor for biological video microscopy. Lecture Notes in Computer Science (PCM), volume 4810, pages 483-493, 2007.

#58: S. J. Julier, J. K. Uhlmann, J. Walters, R. Mittu, and K. Palaniappan

The challenge of scalable and distributed fusion of disparate sources of information

SPIE Proc. Multisensor, Multisource Information Fusion: Architectures, Algorithms and Applications, Volume 6242, pgs. Online, 2006

gis, fusion, parallelization, data mining, remote sensing

Abstract, Bibtex, PlainText, PDF, DOI, Google Scholar

@incollection{Julier:SPIE-2006,
  author = "S. J. Julier and J. K. Uhlmann and J. Walters and R. Mittu and K. Palaniappan",
  title = "The challenge of scalable and distributed fusion of disparate sources of information",
  year = 2006,
  booktitle = "SPIE Proc. Multisensor, Multisource Information Fusion: Architectures, Algorithms and Applications",
  volume = 6242,
  number = 1,
  pages = "Online",
  keywords = "gis, fusion, parallelization, data mining, remote sensing",
  doi = "10.1117/12.666395"
}

S. J. Julier, J. K. Uhlmann, J. Walters, R. Mittu, and K. Palaniappan. The challenge of scalable and distributed fusion of disparate sources of information. SPIE Proc. Multisensor, Multisource Information Fusion: Architectures, Algorithms and Applications, volume 6242, issue 1, pages Online, 2006.

#34: G. Seetharaman, G. Gasperas, and K. Palaniappan

A piecewise affine model for image registration in nonrigid motion analysis

IEEE Int. Conf. Image Processing, Volume 1, pgs. 561--564, 2000

wami, tracking, fmv, registration, motion, fusion, dod

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar

@inproceedings{Guna:ICIP-2000,
  author = "G. Seetharaman and G. Gasperas and K. Palaniappan",
  title = "A piecewise affine model for image registration in nonrigid motion analysis",
  year = 2000,
  booktitle = "IEEE Int. Conf. Image Processing",
  volume = 1,
  pages = "561--564",
  keywords = "wami, tracking, fmv, registration, motion, fusion, dod",
  doi = "10.1109/ICIP.2000.901020",
  url = "http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=901020"
}

G. Seetharaman, G. Gasperas, and K. Palaniappan. A piecewise affine model for image registration in nonrigid motion analysis. IEEE Int. Conf. Image Processing, volume 1, pages 561--564, 2000.

27 publications with the keyword "fusion"

jaw movement, food intake, behavior, neuronal migration, axon guidance, zebrafish, neural circuits, facial branchiomotor neuron, fusion, biomedical

deep learning, fusion, wami, object detection, multi-object tracking, dod

visual object tracking, staple, correlation filter, color name, fusion

3d reconstruction, wami, registration, fusion, fmv, dod

wami, visual events, fusion, data mining, fmv, dod

image enhancement, wami, visual events, fusion, fmv, dod

wami, tracking, fmv, features, motion, fusion, dod

wami, tracking, fmv, features, motion, fusion, dod

wami, tracking, fmv, features, motion, fusion, data mining, machine learning, dod

wami, tracking, fmv, motion, features, fusion, dod

active contours, color, texture, segmentation, features, fusion

wami, tracking, fmv, motion, features, fusion, dod

wami, tracking, fmv, features, motion, fusion, dod

wami, visual events, fusion, data mining, gis, dod

wami, tracking, fmv, motion, features, fusion, dod

fmv, motion, features, fusion, visual events, data mining, cbir

wami, tracking, fmv, registration, motion, fusion, dod

fmv, motion, features, fusion, visual events, data mining, cbir

fmv, features, fusion, visual events, data mining, cbir

fmv, features, fusion, visual events, data mining, cbir

fmv, features, fusion, visual events, data mining, cbir

wami, tracking, fmv, registration, motion, fusion, dod

motion, fusion, tracking, active contours, visual events, features

motion, fusion, tracking, active contours, visual events, features

motion, fusion, tracking, active contours, features

gis, fusion, parallelization, data mining, remote sensing

wami, tracking, fmv, registration, motion, fusion, dod