51 publications with the keyword "motion"


#223: M. Poostchi, H. Aliakbarpour, R. Viguier, F. Bunyak, K. Palaniappan, and G. Seetharaman

Semantic depth map fusion for moving vehicle detection in aerial video

Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, pgs. 32-40, 2016

wami, tracking, fmv, features, motion, image analysis

Abstract, Bibtex, PlainText, PDF, URL, Google Scholar
#216: W. R. Thissell, R. Czajkowski, F. Schrenk, T. Selway, A. J. Ries, S. Patel, P. L. McDermott, R. Moten, R. Rudnicki, G. Seetharaman, I. Ersoy, and K. Palaniappan

A scalable architecture for operational FMV exploitation (AVAA)

Proc. IEEE International Conference on Computer Vision Workshop (ICCVW) Video Summarization for Large-scale Analytics Workshop, 2015

fmv, motion, features, image anlaysis, wami

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#193: M. Kristan, J. Matas, A. Leonardis, M. Felsberg, .., R. Pelapur, K. Palaniappan, F. Bunyak, M. Poostchi, S. Yao, and K. Gao

The Visual Object Tracking VOT2015 challenge results

IEEE International Conference on Computer Vision Workshops (ICCVW), pgs. 564-586, 2015

wami, tracking, fmv, features, motion, image analysis

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#164: R. Pelapur, F. Bunyak, G. Seetharaman, and K. Palaniappan

Vehicle detection and orientation estimation using the Radon transform

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

wami, tracking, fmv, motion, dod

Abstract, Bibtex, PlainText, PDF, DOI, Google Scholar
#173: M. Poostchi, F. Bunyak, and K. Palaniappan

Feature selection for appearance-based vehicle tracking in geospatial video

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

wami, tracking, fmv, features, motion, dod

Abstract, Bibtex, PlainText, PDF, DOI, Google Scholar
#168: J. Fraser, A. Haridas, G. Seetharaman, R. Rao, and K. Palaniappan

KOLAM: A cross-platform architecture for scalable visualization and tracking in wide-area motion imagery

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

visualization, big data, wami, tracking, fmv, features, motion, dod, biomedical

Abstract, Bibtex, PlainText, PDF, DOI, Google Scholar
#160: M. Poostchi, K. Palaniappan, F. Bunyak, M. Becchi, and G. Seetharaman

Efficient GPU implementation of the integral histogram

Lecture Notes in Computer Science (ACCV Workshop on Developer-Centered Computer Vision), Volume 7728, pgs. 266--278, 2012

parallelization, gpu, tracking, fmv, motion, features, dod

Abstract, Bibtex, PlainText, PDF, Google Scholar
#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
#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
#141: I. Ersoy, K. Palaniappan, and G. Seetharaman

Visual tracking with robust target localization

IEEE Int. Conf. Image Processing, pgs. 1365--1368, 2012

wami, tracking, fmv, features, motion, dod

Abstract, Bibtex, PlainText, PDF, Google Scholar
#145: R. Pelapur, K. Palaniappan, and G. Seetharaman

Robust orientation and appearance adaptation for wide-area large format video object tracking

9th IEEE Int. Conf. Advanced Video and Signal-Based Surveillance, 2012

wami, tracking, fmv, motion, features, dod

Abstract, Bibtex, PlainText, PDF, DOI, Google Scholar
#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
#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
#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
#146: M. Poostchi, K. Palaniappan, F. Bunyak, M. Becchi, and G. Seetharaman

Realtime motion detection based on the spatio-temporal median filter using GPU integral histograms

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

parallelization, gpu, tracking, fmv, motion, features, dod

Abstract, Bibtex, PlainText, PDF, DOI, Google Scholar
#150: L. Wang, C. Shen, G. Seetharaman, K. Palaniappan, and S. Bhattacharyya

Multidimensional dataflow graph modeling and mapping for efficient GPU implementation

IEEE Workshop Signal Processing Systems (SiPS), pgs. 300--305, 2012

parallelization, gpu, tracking, fmv, motion, features, dod

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#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
#127: P. Bellens, K. Palaniappan, R. M. Badia, G. Seetharaman, and J. Labarta

Parallel implementation of the integral histogram

Lecture Notes in Computer Science (ACIVS), Volume 6915, pgs. 586--598, 2011

parallelization, gpu, tracking, fmv, motion, features, dod

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#123: A. Haridas, R. Pelapur, J. Fraser, F. Bunyak, and K. Palaniappan

Visualization of automated and manual trajectories in wide-area motion imagery

15th Int. Conf. Information Visualization, pgs. 288--293, 2011

visualization, big data, wami, tracking, fmv, features, motion, dod

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#128: K. Palaniappan, I. Ersoy, G. Seetharaman, S. Davis, P. Kumar, R. M. Rao, and R. Linderman

Parallel flux tensor analysis for efficient moving object detection

14th Int. Conf. Information Fusion, 2011

parallelization, wami, tracking, fmv, motion, dod

Abstract, Bibtex, PlainText, PDF, URL, Google Scholar
#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
#110: K. Palaniappan, I. Ersoy, G. Seetharaman, S. Davis, R. Rao, and R. Linderman

Multicore energy efficient flux tensor for video analysis

IEEE Workshop on Energy Efficient High-Performance Computing (EEHiPC), 2010

parallelization, wami, tracking, fmv, motion, dod

Abstract, Bibtex, PlainText, PDF, URL, Google Scholar
#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
#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
#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
#97: F. Bunyak and K. Palaniappan

Level set-based fast multi-phase graph partitioning active contours using constant memory

Lecture Notes in Computer Science (ACIVS), Volume 5807, pgs. 145--155, 2009

detection, segmentation, active contours, motion, classification

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#99: S. K. Nath and K. Palaniappan

Fast graph partitioning active contours for image segmentation using histograms

EURASIP Journal on Image and Video Processing, pgs. 9p, 2009

detection, segmentation, active contours, motion, classification

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#102: F. Bunyak and K. Palaniappan

Efficient segmentation using feature-based graph partitioning active contours

12th IEEE Int. Conf. Computer Vision, pgs. 873--880, 2009

detection, segmentation, active contours, motion, classification

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#94: P. Kumar, K. Palaniappan, A. Mittal, and G. Seetharaman

Parallel blob extraction using the multi-core Cell processor

Lecture Notes in Computer Science (ACIVS), Volume 5807, pgs. 320--332, 2009

parallelization, tracking, fmv, motion, features, dod

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#93: S. Mehta, A. Misra, A. Singhal, P. Kumar, A. Mittal, and K. Palaniappan

Parallel implementation of video surveillance algorithms on GPU architectures using CUDA

17th IEEE Int. Conf. Advanced Computing and Communications (ADCOM), 2009

parallelization, gpu, tracking, fmv, motion, features, dod

Abstract, Bibtex, PlainText, PDF, Google Scholar
#90: B. Shen, W. Tao, J. Chern, R. Atlas, and K. Palaniappan

Scalability improvements in the NASA Goddard Multiscale Modeling Framework for tropical cyclone climate studies

Proc. 10th Int. Conf. for High-Performance Computing in ASIA-Pacific Region, 2009

visualization, parallelization, features, motion, cloud

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#76: S. Grauer-Gray, C. Kambhamettu, and K. Palaniappan

GPU implementation of belief propagation using CUDA for cloud tracking and reconstruction

5th IAPR Workshop on Pattern Recognition in Remote Sensing (ICPR), pgs. 1--4, 2008

parallelization, gpu, tracking, stereo, fmv, motion, features, cloud

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#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
#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
#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
#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
#41: Y. Zhu, K. Palaniappan, H. Jiang, Y. Zhao, X. Zhuang, and G. Xu

Real-time robust detection and extraction of hand gestures for HCI

IASTED 5th Int. Conf. Computer Graphics and Imaging (CGIM'02), pgs. 68--73, 2002

motion, visual events, tracking, data mining

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#35: L. Zhou, C. Kambhamettu, D. Goldgof, K. Palaniappan, and A. F. Hasler

Tracking non-rigid motion and structure from 2D satellite cloud images without correspondences

IEEE Trans. Pattern Analysis and Machine Intelligence, Volume 23, pgs. 1330--1336, 2001

motion, tracking, parallelization, cloud, remote sensing

Abstract, Bibtex, PlainText, PDF, DOI, Google Scholar
#38: C. Kambhamettu, K. Palaniappan, and A. Hasler

Hierarchical motion decomposition for cloud-tracking

17th Int. AMS Conf. on Interactive Information and Processing Systems (IIPS) for Meteorology, Oceanography and Hydrology, pgs. 318--323, 2001

motion, tracking, parallelization, cloud, remote sensing

Abstract, Bibtex, PlainText, URL, Google Scholar
#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
#27: J. Vass, B. B. Chai, K. Palaniappan, and S. Zhuang

Significance-linked connected component analysis for very low bit-rate wavelet video coding

IEEE Trans. Circuits and Systems for Video Technology, Volume 9, pgs. 630--647, 1999

image compression, image analysis, motion, video coding

Abstract, Bibtex, PlainText, PDF, DOI, Google Scholar
#24: A. F. Hasler, K. Palaniappan, C. Kambhamettu, P. Black, E. Uhlhorn, and D. Chesters

High resolution windfields within the inner core and eye of a mature tropical cyclone from GOES 1-min images

Bulletin of the American Meteorological Society, Volume 79, pgs. 2483--2496, 1998

motion, parallelization, visualization, cloud, big data, remote sensing

Abstract, Bibtex, PlainText, PDF, Google Scholar
#25: J. Vass, K. Palaniappan, and X. Zhuang

Automatic spatio-temporal video sequence segmentation

IEEE Int. Conf. Image Processing, pgs. 958--962, 1998

detection, motion, segmentation, image analysis, color, shape, data mining, cbir

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#20: A. F. Hasler, P. Black, V. M. Karyampudi, M. Jentoft-Nilsen, K. Palaniappan, and D. Chesters

Synthesis of eyewall mesovortex and supercell convective structures in Hurricane Luis with GOES-8/9 stereo, concurrent 1-min GOES-9 and NOAA airborne radar observations

22nd AMS Conf. on Hurricanes and Tropical Meteorology, pgs. 201--202, 1997

motion, parallelization, stereo, cloud, big data, remote sensing

Bibtex, PlainText, Google Scholar
#15: K. Palaniappan, M. Faisal, C. Kambhamettu, and A. F. Hasler

Implementation of an automatic semi-fluid motion analysis algorithm on a massively parallel computer

10th IEEE Int. Parallel Processing Symp., pgs. 864--872, 1996

motion, parallelization, stereo, cloud, big data, remote sensing

Abstract, Bibtex, PlainText, PDF, DOI, Google Scholar
#19: C. Kambhamettu, K. Palaniappan, and A. F. Hasler

Automated cloud-drift winds from GOES images

SPIE Proc. on GOES-8 and Beyond, Volume 2812, pgs. 122--133, 1996

motion, visualization, parallelization, stereo, cloud, big data, remote sensing

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#18: M. Jentoft-Nilsen, K. Palaniappan, A. F. Hasler, and D. Chesters

Enhancement and quality control of GOES images

SPIE Proc. on GOES-8 and Beyond, Volume 2812, pgs. 133--145, 1996

motion, image enhancement, visualization, cloud, big data, remote sensing

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#14: C. Kambhamettu, K. Palaniappan, and A. F. Hasler

Coupled, multi-resolution stereo and motion analysis

IEEE Int. Symp. Computer Vision, pgs. 43--48, 1995

motion, visualization, parallelization, stereo, cloud, big data, remote sensing

Abstract, Bibtex, PlainText, PDF, DOI, Google Scholar
#13: Y. Huang, K. Palaniappan, X. Zhuang, and J. Cavanaugh

Optic flow field segmentation and motion estimation using a robust genetic partitioning algorithm

IEEE Trans. Pattern Analysis and Machine Intelligence, Volume 17, pgs. 1177--1190, 1995

motion, tracking, segmentation, image analysis, machine learning

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#10: K. Palaniappan, C. Kambhamettu, A. F. Hasler, and D. B. Goldgof

Structure and semi-fluid motion analysis of stereoscopic satellite images for cloud tracking

Proc. 5th IEEE Int. Conf. Computer Vision, pgs. 659--665, 1995

motion, tracking, stereo, visualization, cloud, remote sensing

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#12: Y. Huang, K. Palaniappan, X. Zhuang, and J. Cavanaugh

Optic flow segmentation and motion estimation using a robust genetic partitioning algorithm

IEEE Workshop on Nonlinear Signal and Image Processing, pgs. 698--701, 1995

motion, tracking, segmentation, image analysis

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