51 publications with the keyword "tracking"


#315: N. Al-Shakarji, E. Ufuktepe, F. Bunyak, H. Aliakbarpour, G. Seetharaman, and K. Palaniappan

Semi-automatic system for rapid annotation of moving objects in surveillance videos using deep detection and multi-object tracking techniques

IEEE Applied Imagery Pattern Recognition Workshop (AIPR), pgs. 1-6, 2020

ground truth generator, object annotation, deep learning, object detection, tracking

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#282: N. Al-Shakarji, F. Bunyak, G. Seetharaman, and K. Palaniappan

Multi-object tracking cascade with multi-step data association and occlusion handling

IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), pgs. 1-6, 2018

multi-object tracking, tracking, occlusion handling, association

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#275: N. Al-Shakarji, F. Bunyak, G. Seetharaman, and K. Palaniappan

Robust multi-object tracking for wide area motion imagery

IEEE Applied Imagery Pattern Recognition Workshop (AIPR), pgs. 1-5, 2018

tracking, wide area motion imagery, multi-object tracking, tracking-by-detection, data association

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#243: N. Al-Shakarji, F. Bunyak, G. Seetharaman, and K. Palaniappan

Vehicle tracking in wide area motion imagery using KC-LoFT multi-feature discriminative modeling

IEEE Applied Imagery Pattern Recognition Workshop (AIPR), pgs. 1-6, 2017

tracking, wide area motion imagery, kernelized correlation filter, discriminative modeling, ridge regression

Abstract, Bibtex, PlainText, PDF, DOI, Google Scholar
#251: N. Al-Shakarji, F. Bunyak, G. Seetharaman, and K. Palaniappan

Robust multi-object tracking with semantic color correlation

IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), pgs. 1-7, 2017

image color analysis, tracking, color, correlation, lighting, histograms.

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#245: S. Lyui, M. Chang, D. Du, L. Wen, H. Qi, Y. Li, Y. Wei, L. K., T. Hu, M. DelCoco, P. Carcagnì, D. Anisimov, E. Bochinski, F. Galasso, F. Bunyak, G. Han, H. Ye, H. Wang, K. Palaniappan, K. Ozcan, L. W. L. Wang, M. Lauer, N. Watcharapinchai, N. Song, N. Al-Shakarji, S. Wang, S. Amin, S. Rujikietgumjorn, T. Khanova, T. Sikora, T. Kutschbach, V. Eiselein, W. Tian, X. Xue, X. Yu, Y. Lu, Y. Zheng, Y. Huang, and Y. Zhang

UA-DETRAC 2017: Report of AVSS2017 & IWT4S challenge on advanced traffic monitoring

IEEE AVSS International Workshop on Traffic and Street Surveillance for Safety and Security (IWT4S), pgs. 1-7, 2017

multi-object tracking, tracking

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#230: K. Palaniappan, M. Poostchi, H. Aliakbarpour, R. Viguier, J. Fraser, F. Bunyak, A. Basharat, S. Suddarth, E. Blasch, R. Rao, and G. Seetharaman

Moving object detection for vehicle tracking in wide area motion imagery using 4D filtering

Proc. IEEE International Conference on Pattern Recognition (ICPR), 2016

wami, tracking

Abstract, Bibtex, PlainText, URL, Google Scholar
#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
#239: N. Al-Shakarji, F. Bunyak, and K. Palaniappan

CS-LOFT: Color and scale adaptive tracking using Bhattacharyya distance and max pooling consistency

IEEE Applied Imagery Pattern Recognition Workshop (AIPR), 2016

color, tracking, features, single object tracking

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#224: P. Calyam, D. Chemodanov, R. Pelapur, and K. Palaniappan

Regional-scale incident-supporting visual cloud computing with software-defined networking

Proc. SPIE Conf. Geospatial Informatics, Fusion, and Motion Video Analytics VI, 2016

cloud computing, resource management, tracking

Abstract, Bibtex, PlainText, Google Scholar
#232: R. Gargees, B. Morago, R. Pelapur, D. Chemodanov, P. Calyam, Z. Oraibi, Y. Duan, G. Seetharaman, and K. Palaniappan

Incident-supporting visual cloud computing utilizing software-defined networking

IEEE Transactions on Circuits and Systems for Video Technology, 2016

cloud computing, resource management, tracking

Abstract, Bibtex, PlainText, PDF, 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
#178: A. Gning, W. T. L. Teacy, R. Pelapur, H. AliAkbarpour, K. Palaniappan, G. Seetharaman, and S. J. Julier

The effect of state dependent probability of detection in multitarget tracking applications

Proc. SPIE Conf. Geospatial InfoFusion and Video Analytics IV; and Motion Imagery for ISR and Situational Awareness II (Defense, Security and Sensing), Volume 9089, 2014

tracking, multitarget, dod

Abstract, Bibtex, PlainText, PDF, 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
#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
#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
#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
#51: K. Palaniappan, H. S. Jiang, and T. I. Baskin

Non-rigid motion estimation using the robust tensor method

IEEE CVPR Workshop on Articulated and Nonrigid Motion, Volume 1, pgs. 25--33, 2004

detection, segmentation, features, tracking, convex relaxation, plants, biomedical

Abstract, Bibtex, PlainText, PDF, URL, DOI, Google Scholar
#48: C. Weele, H. Jiang, K. K. Palaniappan, V. B. Ivanov, K. Palaniappan, and T. I. Baskin

A new algorithm for computational image analysis of deformable motion at high spatial and temporal resolution applied to root growth: Roughly uniform elongation in the meristem and also, after an abrupt acceleration, in the elongation zone

Plant Physiology, Volume 132, pgs. 1138--1148, 2003

detection, segmentation, features, tracking, plants, biomedical

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#49: H. S. Jiang, K. Palaniappan, and T. I. Baskin

A combined matching and tensor method to obtain high fidelity velocity fields from image sequences of the non-rigid motion of the growth of a plant root

IASTED Int. Conf. on Biomedical Engineering, pgs. 159--165, 2003

detection, segmentation, features, tracking, convex relaxation, plants, biomedical

Abstract, Bibtex, PlainText, URL, 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
#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
#2: K. Palaniappan and H. K. Kesavan

Iterative entropic measures for model order selection

Proc. IEEE Int. Conf. Computers, Systems and Signal Processing, pgs. 1765--1772, 1984

features, detection, tracking

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