Seyler, A.J.,
Real-Time Recording of Television Frame Difference Areas,
PIEEE(51), No. 3, March 1963, pp. 478-480.
BibRef
6303
Seyler, A.J.,
Statistics of Television Frame Differences,
PIEEE(53), No. 12, December 1965, pp. 2127-2128.
BibRef
6512
Candy, J.C.,
Franke, M.A.,
Haskell, R.G.,
Mounts, F.W.,
Transmitting Television As Clusters of Frame-to-Frame Differences,
Bell System Tech.(50), No. 6, July/August 1971, pp. 1889-1919.
BibRef
7107
Onoe, M.,
Hamano, N.,
Ohba, K.,
Computer Analysis of Traffic Flow Observed by Subtractive Television,
CGIP(2), 1973, pp. 377-392.
BibRef
7300
Onoe, M.,
Saito, M.,
Automatic Threshold Setting for the Sequential Similarity Detection
Algorithm,
TC(25), 1976, pp. 1052-1053.
(Or 24 in 1975??)
BibRef
7600
Nagel, H.H.,
Formation of an Object Concept by Analysis of Systematic
Time Variations in the Optically Perceptible Environment,
CGIP(7), No. 2, April 1978, pp. 149-194.
WWW Version.
Motion, Differencing. Find simple objects that are moving smoothly in
front of a contrasting background. This is the basic original paper for
differencing for object recognition.
BibRef
7804
Nagel, H.H.,
Representation of Moving Rigid Objects Based on Visual Observations,
Computer(14), No. 8, August 1981, pp. 29-39.
Basic outline of the Hamburg work - derive 3-D
descriptions from a sequence of 2-D images - derive a series of possible 3-D
objects from sets of 2-D (each 2-D gives a partial 3-D object).
BibRef
8108
Hsu, Y.Z.,
Nagel, H.H., and
Rekers, G.,
New Likelihood Test Methods for Change Detection in Image Sequences,
CVGIP(26), No. 1, April 1984, pp. 73-106.
WWW Version. The image is modeled as patches with intensity determined by a
polynomial of the pixel coordinates. The difference between
successive images is computed using the modeled images. This
eliminates much of the noise associated with straight forward
differencing.
BibRef
8404
Yalamanchili, S.,
Martin, W.N.,
Aggarwal, J.K.,
Extraction of Moving Object Descriptions via Differencing,
CGIP(18), No. 2, February 1982, pp. 188-201.
WWW Version.
BibRef
8202
Earlier:
Differencing Operations for the Segmentation of Moving Objects
in Dynamic Scenes,
ICPR80(1239-1242).
BibRef
Yalamanchili, S.,
Aggarwal, J.K.,
Motion and Image Differencing,
PRIP81(211-216).
BibRef
8100
Yoda, H.[Haruo],
Motoike, J.[Jun],
Visual information processing apparatus,
US_Patent4,346,405, 08/24/1982.
HTML Version.
BibRef
8208
Earlier:
Image data processor,
US_Patent4,254,400, 03/03/1981.
HTML Version. Frame to frame change detection.
BibRef
Jain, R.C.,
Difference and Accumulative Difference Pictures in
Dynamic Scene Analysis,
IVC(2), No. 2, May 1984, pp. 99-108.
WWW Version.
BibRef
8405
Knoll, T.F.,
Delp, E.J.,
Adaptive Gray Scale Mapping to Reduce Registration Noise in
Difference Images,
CVGIP(33), No. 2, February 1986, pp. 129-137.
WWW Version.
BibRef
8602
Lo, T.K.[Thomas K.],
Sacks, J.M.[Jack M.],
Banh, N.D.[Nam D.],
Segmentation method for use against moving objects,
US_Patent5,109,435, 04/28/1992.
HTML Version. Based on background.
BibRef
9204
Banh, N.D.[Nam D.],
Lo, T.K.[Thomas K.],
Holthaus, K.D.[Kelly D.],
Sacks, J.M.[Jack M.],
Moving target detection method using two-frame subtraction and a
two quadrant multiplier,
US_Patent5,150,426, 09/22/1992.
HTML Version.
BibRef
9209
Abe, S.[Shozo],
Apparatus for extracting/combining change region in
image corresponding to moving object,
US_Patent5,099,324, 03/24/1992.
HTML Version.
BibRef
9203
Westberg, L.,
Hierarchical Contour-Based Segmentation of Dynamic Scenes,
PAMI(14), No. 9, September 1992, pp. 946-952.
IEEE Abstract. IEEE Top Reference.
WWW Version. Assume one coherent moving object on the background,
use pyramid based technique and boundaries.
Build on temporal frame differences, detect, object, background,
boundary regions.
BibRef
9209
Bergen, J.R.,
Burt, P.J.,
Hingorani, R., and
Peleg, S.,
A Three-Frame Algorithm for Estimating Two-Component Image Motion,
PAMI(14), No. 9, September 1992, pp. 886-896.
IEEE Abstract. IEEE Top Reference.
WWW Version.
BibRef
9209
Earlier:
Computing Two Motions from Three Frames,
ICCV90(27-32).
WWW Version.
Motion, Three frames. Two components are background motion and single object
motion. Find the background motion and use it to detect the other moving
objects by simple differencing.
BibRef
Burt, P.J.,
Hingorani, R., and
Kolczynski, R.J.,
Mechanisms for Isolating Component Patterns in the Sequential Analysis of
Multiple Motion,
Motion91(187-193).
Region by region motion estimation to find single motions,
use for stabilization.
BibRef
9100
Burt, P.J.,
Bergen, J.R.,
Hingorani, R.,
Kolczynski, R.J.,
Lee, W.A.,
Leung, A.,
Lubin, J., and
Shvaytser, H.,
Object Tracking with a Moving Camera,
Motion89(2-12).
Image differencing with global tracking to get moving
objects separately.
BibRef
8900
Sauer, K.[Ken],
Jones, C.[Coleen],
Bayesian Block-Wise Segmentation of Interframe Differences in
Video Sequences,
GMIP(55), No. 2, March 1993, pp. 129-yy.
BibRef
9303
Rathi, R.P.[Rajendra P.],
Method and apparatus for monitoring traffic flow,
US_Patent5,296,852, 03/22/1994.
HTML Version. Vehicle where difference between image and reference exceeds threshold.
BibRef
9403
Bichsel, M.,
Segmenting Simply Connected Moving-Objects In A Static Scene,
PAMI(16), No. 11, November 1994, pp. 1138-1142.
IEEE Abstract. IEEE Top Reference.
WWW Version. Uses object-background probability and connectedness.
BibRef
9411
Florent, R.[Raoul],
Device for the detection of objects in a sequence of images,
US_Patent5,583,947, 12/10/1996.
HTML Version.
BibRef
9612
Earlier:
Method and device for use in detecting moving targets,
US_Patent5,406,501, 04/11/1995,
HTML Version. differences of registered images.
BibRef
Fan, J.P.,
Wang, R.,
Zhang, L.M.,
Xing, D.J.,
Gan, F.X.,
Image Sequence Segmentation Based on 2D Temporal Entropic Thresholding,
PRL(17), No. 10, September 2 1996, pp. 1101-1107.
Frame Difference Contrast, Local Variance Contrast.
BibRef
9609
Ghali, A.,
Daemi, M.F.,
Alkhateeb, K.A.,
Information-Based Image Dissimilarity Measure,
OptEng(37), No. 3, March 1998, pp. 808-812.
9804
BibRef
Ghali, A.,
Daemi, M.F.,
Mansour, M.,
Image Structural Information Assessment,
PRL(19), No. 5-6, April 1998, pp. 447-453.
9808
BibRef
Ghali, A.,
Daemi, M.F.,
Information-based shape description with scale, translation and
rotation invariance,
ICIP96(III: 611-614).
WWW Version.
9610
BibRef
And:
Recognition Information,
ICPR96(I: 544-548).
WWW Version.
9608(CIMI, UK)
BibRef
Yoon, S.C.,
Ratakonda, K.,
Ahuja, N.,
Low Bit-Rate Video Coding with Implicit Multiscale Segmentation,
CirSysVideo(9), No. 7, October 1999, pp. 1115.
IEEE Top Reference. See also Lossless image compression with multiscale segmentation.
BibRef
9910
Ratakonda, K.,
Yoon, S.C., and
Ahuja, N.,
Coding the Displaced Frame Difference for Video Compression,
ICIP97(I: 353-356).
WWW Version.
BibRef
9700
Ratakonda, K.[Krishna],
Ahuja, N.,
Segmentation Based Reversible Image Compression,
ICIP96(I: 81-84).
WWW Version.
BibRef
9600
Yoon, S.,
Ratakonda, K., and
Ahuja, N.,
Region-Based Video Coding Using a Multiscale Image Segmentation,
ICIP97(II: 510-513).
WWW Version.
BibRef
9700
Sawhney, H.S.[Harpreet S.],
Guo, Y.[Yanlin],
Kumar, R.[Rakesh],
Independent Motion Detection in 3D Scenes,
PAMI(22), No. 10, October 2000, pp. 1191-1199.
IEEE Abstract. IEEE Top Reference.
WWW Version.
0011
BibRef
Earlier:
Add A3:
Asmuth, J.,
ICCV99(612-619).
WWW Version. Tracking for surveillance. An image differencing method.
BibRef
Hui, K.C.[Ko-Cheung],
Siu, W.C.[Wan-Chi],
Extended Analysis of Motion-Compensated Frame Difference for
Block-Based Motion Prediction Error,
IP(16), No. 5, May 2007, pp. 1232-1245.
WWW Version.
0704
BibRef
Migliore, D.A.[Davide A.],
Matteucci, M.[Matteo],
Naccari, M.[Matteo],
A revaluation of frame difference in fast and robust motion detection,
VSSN06(215-218).
WWW Version.
0701
BibRef
Archetti, F.[Francesco],
Manfredotti, C.E.[Cristina E.],
Messina, V.[Vincenzina],
Sorrenti, D.G.[Domenico G.],
Foreground-to-Ghost Discrimination in Single-Difference Pre-processing,
ACIVS06(263-274).
WWW Version.
0609frame differencing, false foregrounds.
BibRef
Sangi, P.,
Heikkila, J.,
Silven, O.,
Motion analysis using frame differences with spatial gradient measures,
ICPR04(IV: 733-736).
WWW Version.
0409
BibRef
Caplier, A.,
Bonnaud, L.,
Chassery, J.M.,
Robust Fast Extraction of Video Objects Combining Frame Differences and
Adaptive Reference Image,
ICIP01(II: 785-788).
IEEE Abstract. IEEE Top Reference.
0108
BibRef
Kurianski, A.[Adam],
Nieniewski, M.[Mariusz],
Hidden MRF detection of motion of objects with uniform brightness,
CIAP95(656-662).
WWW Version.
9509
BibRef
Shio, A., and
Sklansky, J.,
Segmentation of People in Motion,
Motion91(325-332).
Get background via a mode filter over the sequence, then differences
between frame and background to get the moving people.
BibRef
9100
Bhat, K.S.[Kiran S.],
Saptharishi, M.[Mahesh],
Khosla, P.K.[Pradeep K.],
Motion Detection and Segmentation Using Image Mosaics,
ICME00(WP6).
0007
BibRef
Singer, S., and
Huberman, B.A.,
Concurrent, Fault Tolerant Detection of 2-D Motion,
DraftDoesn't say much more than a detector
array with differences and tracking the differences of neighbors.
BibRef
0000
Chapter on Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion continues in
Differencing Papers -- Ramesh Jain .