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Palaniappan, K., Rao, R., and Seetharaman, G., ́Wide-area persistent airborne video: Architecture and challenges, " in [Distributed Video Sensor Networks: Research Challenges and Future Directions], Banhu, B., Ravishankar, C. V., Roy-Chowdhury, A. K., Aghajan, H., and Terzopoulos, D., eds., ch. 24, 349-371, Springer (2011).
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Efficient feature extraction and likelihood fusion for vehicle tracking in low frame rate airborne video
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Palaniappan, K., Bunyak, F., Kumar, P., Ersoy, I., Jaeger, S., Ganguli, K., Haridas, A., Fraser, J., Rao, R., and Seetharaman, G., ́Efficient feature extraction and likelihood fusion for vehicle tracking in low frame rate airborne video, " in [13th Int. Conf. Information Fusion], (2010).
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3
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80052975098
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Visualization of automated and manual trajectories in wide-area motion imagery
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Haridas, A., Pelapur, R., Fraser, J., Bunyak, F., and Palaniappan, K., ́Visualization of automated and manual trajectories in wide-area motion imagery, " in [15th Int. Conf. Information Visualization], 288-293 (2011).
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KOLAM: An extensible cross-platform architecture for visualization and tracking in wide-area motion imagery
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Fraser, J., Haridas, A., Seetharaman, G., Rao, R., and Palaniappan, K., ́KOLAM: An extensible cross- platform architecture for visualization and tracking in wide-area motion imagery, " in [Proc. SPIE Conf. Geospatial InfoFusion II (Defense, Security and Sensing: Sensor Data and Information Exploitation)], 8396 (2012).
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84860758901
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Contemporary concerns in geographical/Geospatial Information Systems (GIS) processing
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Blasch, E., Deignan, P., Dockstader, S., Pellechia, M., Palaniappan, K., and Seetharaman, G., ́Contemporary concerns in geographical/geospatial information systems (GIS) processing, " in [Proc. IEEE National Aerospace and Electronics Conference (NAECON)], 183-190 (2011).
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Wide-area motion imagery
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Porter, R., Fraser, A. M., and Hush, D., ́Wide-area motion imagery, " IEEE Signal Processing Magazine 27(5), 56-65 (2010).
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Evaluation of visual tracking in extremely low frame rate wide area motion imagery
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Ling, H. and et al., ́Evaluation of visual tracking in extremely low frame rate wide area motion imagery, " in [14th Int. Conf. on Information Fusion], 1866-1873 (2011).
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Ling, H.A.1
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UAV-video registration using block-based features
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Hafiane, A., Palaniappan, K., and Seetharaman, G., ́UAV-video registration using block-based features, " in [IEEE Int. Geoscience and Remote Sensing Symposium], II, 1104-1107 (2008).
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IEEE Int. Geoscience and Remote Sensing Symposium
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AFRL CLIF dataset OSU, ́https://www.sdms.afrl.af.mil/index.php? collection=clif2007, " (2007).
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AFRL CLIF Dataset OSU
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Persistent target tracking using likelihood fusion in wide-area and full motion video sequences
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Pelapur, R., Candemir, S., Poostchi, M., Bunyak, F., Wang, R., Seetharaman, G., and Palaniappan, K., ́Persistent target tracking using likelihood fusion in wide-area and full motion video sequences, " in [15th Int. Conf. Information Fusion], (2012).
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Online selection of discriminative tracking features
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Feature selection for appearance-based vehicle tracking in geospatial video
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Poostchi, M., Bunyak, F., and Palaniappan, K., ́Feature selection for appearance-based vehicle tracking in geospatial video, " in [Proc. SPIE Conf. Geospatial InfoFusion II (Defense, Security and Sensing: Sensor Data and Information Exploitation)], 8396 (2012).
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Yin, Z., Porikli, F., and Collins, R., ́Likelihood map fusion for visual object tracking, " in [IEEE Workshop Appl. Comput. Vis.], 1-7 (2008).
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The challenge of scalable and distributed fusion of disparate sources of information
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Julier, S. J., Uhlmann, J. K., Walters, J., Mittu, R., and Palaniappan, K., ́The challenge of scalable and distributed fusion of disparate sources of information, " in [SPIE Proc. Multisensor, Multisource Information Fusion: Architectures, Algorithms and Applications], 6242(1), Online (2006).
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Geodesic active contour based fusion of visible and infrared video for persistent object tracking
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Bunyak, F., Palaniappan, K., Nath, S. K., and Seetharaman, G., ́Flux tensor constrained geodesic active contours with sensor fusion for persistent object tracking, " J. Multimedia 2, 20-33 (August 2007).
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Adaptive multi-feature tracking in a particle filtering frame- work
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Maggio, E., Smeraldi, F., and Cavallaro, A., ́Adaptive multi-feature tracking in a particle filtering frame- work, " IEEE Trans. on Circuits and Systems for Video Technology 17, 1348-1359 (2007).
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Rotationally invariant hashing of median patterns for texture classification
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Hafiane, A., Seetharaman, G., Palaniappan, K., and Zavidovique, B., ́Rotationally invariant hashing of median patterns for texture classification, " Lecture Notes in Computer Science (ICIAR) 5112, 619-629 (2008).
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Adaptive robust structure tensors for orientation estimation and image segmentation
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Nath, S. and Palaniappan, K., ́Adaptive robust structure tensors for orientation estimation and image segmentation, " Lecture Notes in Computer Science (ISVC) 3804, 445-453 (2005).
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Moving object segmentation using the UX tensor for biological video microscopy
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Palaniappan, K., Ersoy, I., and Nath, S. K., ́Moving object segmentation using the ux tensor for biological video microscopy, " Lecture Notes in Computer Science (PCM) 4810, 483-493 (2007).
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A piecewise affine model for image registration in 3-D motion analysis
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Seetharaman, G., Gasperas, G., and Palaniappan, K., ́A piecewise affine model for image registration in 3-D motion analysis, " in [IEEE Int. Conf. Image Processing], 561-564 (2000).
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Accurate spatial neighborhood relationships for arbitrarily- shaped objects using Hamilton-Jacobi GVD
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Nath, S. K., Palaniappan, K., and Bunyak, F., ́Accurate spatial neighborhood relationships for arbitrarily- shaped objects using Hamilton-Jacobi GVD, " Lecture Notes in Computer Science (SCIA) 4522, 421-431 (2007).
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Cell segmentation using coupled level sets and graph-vertex coloring
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Nath, S. K., Palaniappan, K., and Bunyak, F., ́Cell segmentation using coupled level sets and graph-vertex coloring, " Lecture Notes in Computer Science (MICCAI) 4190, 101-108 (2006).
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Efficient segmentation using feature-based graph partitioning active contours
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Parallel blob extraction using the multi-core Cell processor
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Parallel implementation of video surveillance algorithms on GPU architectures using CUDA
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Parallel implementation of the integral histogram
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