Mutch, K.M.[Kathleen M.], and
Thompson, W.B.[William B.],
Analysis of Accretion and Deletion at Boundaries in Dynamic Scenes,
PAMI(7), No. 2, March 1985, pp. 133-138.
BibRef
8503
Earlier:
Univ. of MinnesotaTR 84-7, Computer Science Dept, May 1984.
Analysis of the changes (adding and removing) in regions at
boundaries when one object moves relative to the other. This can
give the optic flow data for the region near the boundary.
BibRef
Thompson, W.B.,
Combining Motion and Contrast for Segmentation,
PAMI(2), No. 6, November 1980, pp. 543-549.
Brightness is used for static segmentation then
merge regions based on motion similarities.
See also Velocity Determination in Scenes Containing Several Moving Objects.
BibRef
8011
Thompson, W.B., and
Pong, T.C.,
Detecting Moving Objects,
IJCV(4), No. 1. January 1990, pp. 39-58.
Springer DOI
BibRef
9001
Earlier:
ICCV87(201-208).
Several different restricted techniques are developed
for motion detection using camera motion or scene structure and flow fields.
BibRef
Kim, B.G.[Byung-Gyu],
Kim, D.J.[Do-Jong],
Park, D.J.[Dong-Jo],
Novel precision target detection with adaptive thresholding for dynamic
image segmentation,
MVA(12), No. 5, 2001, pp. 259-270.
Springer DOI
0103
See also Fast image segmentation based on multi-resolution analysis and wavelets.
BibRef
Kim, B.G.[Byung-Gyu],
Park, D.J.[Dong-Jo],
Novel target segmentation and tracking based on fuzzy membership
distribution for vision-based target tracking system,
IVC(24), No. 12, 1 December 2006, pp. 1319-1331.
Elsevier DOI
0610
Image segmentation, Target detection, Three-dimensional feature;
Fuzzy membership value, Optimal membership value
BibRef
Kim, B.G.[Byung-Gyu],
Park, D.J.[Dong-Jo],
Novel Noncontrast-Based Edge Descriptor for Image Segmentation,
CirSysVideo(16), No. 9, September 2006, pp. 1086-1095.
IEEE DOI
0610
BibRef
Kim, B.G.[Byung-Gyu],
Park, D.J.[Dong-Jo],
Unsupervised video object segmentation and tracking based on new edge
features,
PRL(25), No. 15, November 2004, pp. 1731-1742.
Elsevier DOI
0411
Track regions for coding applications.
BibRef
Kim, B.G.[Byung-Gyu],
Mah, P.S.[Pyeong-Soo],
Park, D.J.[Dong-Jo],
Jung, J.H.[Jik-Han],
Park, J.S.[Ju-Seok],
Non-contrast based edge descriptor for image segmentation,
ICPR04(I: 572-575).
IEEE DOI
0409
BibRef
Pundlik, S.J.[Shrinivas J.],
Birchfield, S.T.[Stanley T.],
Real-Time Motion Segmentation of Sparse Feature Points at Any Speed,
SMC-B(37), No. 3, June 2007, pp. 731-742.
IEEE DOI
0711
BibRef
Earlier:
Motion Segmentation at Any Speed,
BMVC06(I:427).
PDF File.
0609
BibRef
Pundlik, S.J.[Shrinivas J.],
Birchfield, S.T.[Stanley T.],
Motion-Based View-Invariant Articulated Motion Detection and Pose
Estimation Using Sparse Point Features,
ISVC09(I: 425-434).
Springer DOI
0911
BibRef
Earlier:
Joint tracking of features and edges,
CVPR08(1-6).
IEEE DOI
0806
BibRef
Direkoglu, C.[Cem],
Nixon, M.S.[Mark S.],
Moving-edge detection via heat flow analogy,
PRL(32), No. 2, 15 January 2011, pp. 270-279.
Elsevier DOI
1101
BibRef
And:
Shape Extraction Via Heat Flow Analogy,
ACIVS07(553-564).
Springer DOI
0708
BibRef
Earlier:
Low Level Moving-Feature Extraction Via Heat Flow Analogy,
ISVC06(I: 243-252).
Springer DOI
0611
Moving-edges, Feature extraction, Image processing, Heat flow
BibRef
Direkoglu, C.[Cem],
Nixon, M.S.[Mark S.],
Shape classification via image-based multiscale description,
PR(44), No. 9, September 2011, pp. 2134-2146.
Elsevier DOI
1106
BibRef
Earlier:
Image-Based Multiscale Shape Description Using Gaussian Filter,
ICCVGIP08(673-678).
IEEE DOI
0812
Shape classification, Fourier-based description, Multiscale
representation, Gaussian filter, Feature extraction
BibRef
Subudhi, B.N.[Badri Narayan],
Nanda, P.K.[Pradipta Kumar],
Ghosh, A.[Ashish],
A Change Information Based Fast Algorithm for Video Object Detection
and Tracking,
CirSysVideo(21), No. 7, July 2011, pp. 993-1004.
IEEE DOI
1107
BibRef
Subudhi, B.N.[Badri Narayan],
Nanda, P.K.[Pradipta Kumar],
Ghosh, A.[Ashish],
Entropy based region selection for moving object detection,
PRL(32), No. 15, 1 November 2011, pp. 2097-2108.
Elsevier DOI
1112
Object detection, MAP estimation, Simulated annealing, Entropy;
Thresholding, Gaussian distribution
See also Change detection for moving object segmentation with robust background construction under Wronskian framework.
See also Integration of Gibbs Markov Random Field and Hopfield-Type Neural Networks for Unsupervised Change Detection in Remotely Sensed Multitemporal Images.
BibRef
Subudhi, B.N.[Badri Narayan],
Veerakumar, T.,
Esakkirajan, S.,
Ghosh, A.[Ashish],
Kernelized Fuzzy Modal Variation for Local Change Detection From
Video Scenes,
MultMed(22), No. 4, April 2020, pp. 912-920.
IEEE DOI
2004
Principal component analysis, Surveillance, Kernel, Visualization,
Probability density function, Object detection, Jamming,
modal variation
BibRef
Ghosh, A.[Ashish],
Subudhi, B.N.[Badri Narayan],
Ghosh, S.,
Object Detection From Videos Captured by Moving Camera by Fuzzy Edge
Incorporated Markov Random Field and Local Histogram Matching,
CirSysVideo(22), No. 8, August 2012, pp. 1127-1135.
IEEE DOI
1208
BibRef
Subudhi, B.N.[Badri Narayan],
Nanda, P.K.[Pradipta Kumar],
An Evolutionary Based Slow and Fast Moving Video Object Detection
Scheme Using Compound Markov Random Field Model,
ICCVGIP08(398-405).
IEEE DOI
0812
BibRef
Panda, S.[Sucheta],
Nanda, P.K.,
Unsupervised Color Image Segmentation Using Compound Markov Random
Field Model,
PReMI09(291-296).
Springer DOI
0912
BibRef
Yang, Y.C.[Ying-Chun],
Peng, Y.C.[Yu-Chen],
Han, S.D.[Shou-Dong],
Video segmentation based on patch matching and enhanced Onecut,
ICIVC17(346-350)
IEEE DOI
1708
Color, Image color analysis, Image edge detection, Optical imaging,
Optical noise, Optical sensors, Shape, enhanced onecut,
local classifier, patch matching, video, segmentation
BibRef
Vantaram, S.R.[Sreenath Rao],
Saber, E.[Eli],
Unsupervised video segmentation by dynamic volume growing and
multivariate volume merging using color-texture-gradient features,
ICIP12(305-308).
IEEE DOI
1302
BibRef
Danielsson, O.[Oscar],
Carlsson, S.[Stefan],
Generic Object Class Detection Using Feature Maps,
SCIA11(348-359).
Springer DOI
1105
BibRef
Earlier:
Generic Object Class Detection Using Boosted Configurations of Oriented
Edges,
ACCV10(II: 1-14).
Springer DOI
1011
BibRef
Danielsson, O.[Oscar],
Carlsson, S.[Stefan],
Sullivan, J.[Josephine],
Automatic learning and extraction of multi-local features,
ICCV09(917-924).
IEEE DOI
0909
BibRef
Earlier:
Object Detection Using Multi-local Feature Manifolds,
DICTA08(612-618).
IEEE DOI
0812
Each feature a collection of local features.
BibRef
Zhang, J.S.[Jia-Shu],
Zhang, L., and
Tai, H.M.[Heng-Ming],
Efficient video object segmentation using adaptive background registration
and edge-based change detection techniques,
ICME04(II: 1467-1470).
BibRef
0400
Hwang, T.L.,
Clark, J.J.[James J.],
On local detection of moving edges,
ICPR90(I: 180-184).
IEEE DOI
9006
BibRef
Chapter on Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion continues in
Moving Object Extraction with Moving Cameras .