Keith Price Bibliography Obstacle Detection, Time to Collision Techniques

17.6.3 Obstacle Detection, Time to Collision Techniques

Chapter Contents (Back)
Obstacle Detection. Collision Detection. Time to Collision. See also Road, Path Following Operators, Obstacles.

Goodrich, G.W.[George W.],
Collision avoidance using optical pattern growth rate,
US_Patent4,257,703, 03/24/1981.
HTML Version. Basically looming. BibRef 8103

Sawhney, H.S., and Hanson, A.R.,
Trackability as a Cue for Potential Obstacle Identification and 3-D Description,
IJCV(11), No. 3, December 1993, pp. 237-265.
Springer DOI Reference BibRef 9312
And: UMass-TR-92-15, February 1992. BibRef
Earlier:
Affine Trackability Aids Obstacle Detection,
CVPR92(418-424).
IEEE Abstract. IEEE Top Reference. BibRef
And:
Tracking, Detection and 3D Representation of Potential Obstacles Using Affine Constraints,
DARPA92(1009-1017). BibRef
Earlier:
Identification and 3D Description of 'Shallow' Environmental Structure in a Sequence of Images,
CVPR91(179-185).
IEEE Abstract. IEEE Top Reference. Shallow objects (mostly flat in depth), 3-D reconstructions and segmentation of the objects. BibRef

Sawhney, H.S.,
Simplifying Motion and Structure Analysis Using Planar Parallax and Image Warping,
ICPR94(A:403-408).
IEEE DOI Reference BibRef 9400
And:
3D Geometry from Planar Parallax,
CVPR94(929-934).
IEEE Abstract. IEEE Top Reference. BibRef

Kumar, R., Sawhney, H.S., and Hanson, A.R.,
3D Model Acquisition from Monocular Image Sequences,
CVPR92(209-215).
IEEE Abstract. IEEE Top Reference. BibRef 9200
And: UMassCS-TR-93-5, January 1993. Extending the shallow structure work with refinement of the structure. BibRef

Sawhney, H.S., Kumar, R., and Hanson, A.R., Riseman, E.M.,
Landmark-Based Navigation-Model Extension and Refinement,
UMass-CS-TR-93-6, January 1993. See also Landmark-Based Navigation and the Acquisition of Environmental Models. BibRef 9301
And:
Model Extension and Refinement Using Landmarks,
DARPA93(507-514). BibRef

Kumar, R.,
Model Dependent Inference of 3D Information from a Sequence of 2D Images,
COINS- TR-92-04, 1992, BibRef 9200 Ph.D. BibRef

Ringach, D.L., and Baram, Y.,
A Diffusion Mechanism for Obstacle Detection from Size-Change Information,
PAMI(16), No. 1, January 1994, pp. 76-80.
IEEE Abstract. IEEE Top Reference.
WWW Version. Obstacles are indicated by the size change effects. BibRef 9401

Meyer, F.G.,
Time-to-Collision from First-Order Models of the Motion Field,
RA(10), 1994, pp. 792-798. BibRef 9400

Meyer, F., Bouthemy, P.,
Estimation of Time-to-Collision Maps from First Order Motion Models and Normal Flows,
ICPR92(I:78-82).
IEEE DOI Reference BibRef 9200

Ancona, N.[Nicola], Poggio, T.[Tomaso],
Optical Flow from 1-D Correlation: Application to a Simple Time-to-Crash Detector,
IJCV(14), No. 2, March 1995, pp. 131-146.
Springer DOI Reference BibRef 9503
Earlier: ICCV93(209-214).
IEEE DOI Reference BibRef
And: MIT AI Memo-1375, October 1993.
WWW Version. BibRef
And: Add A2 Horn, B.K.P., DARPA93(673-682). Computations only in 1-D. BibRef

Ancona, N.,
A Fast Obstacle Detection Method Based on Optical Flow,
ECCV92(267-271).
Springer DOI Reference BibRef 9200

Hatsopoulos, N., Gabbiani, F., and Laurent, G.,
Elementary Computation of Object Approach by a Wide-Field Visual Neuron,
Science(270), November 10, 1995, pp. 1000-1003. Has the standard references to biological issues in optical flow and related topics. Not computer vision, but in a locust, a neuron's response is described by multiplying the velocity of the image edge with an exponential function of the size of the object's image on the retina. The product peaks before impact, thus the locust can anticipate collision. BibRef 9511

Burlina, P.[Philippe], and Chellappa, R.[Rama],
Analyzing Looming Motion Components from Their Spatiotemporal Spectral Signature,
PAMI(18), No. 10, October 1996, pp. 1029-1033.
IEEE Abstract. IEEE Top Reference.
WWW Version. 9611 Time to Collision. BibRef
Earlier:
Spectral and Temporal Representations of Looming and Maneuvering Information,
ARPA94(II:1199-1207). BibRef
And:
Spatio-temporal moments and generalized spectral analysis of divergent images for motion estimation,
ICIP94(I: 328-332).
IEEE DOI Reference 9411 BibRef
And:
Time-to-X: Analysis of Motion through Temporal Parameters,
CVPR94(461-468).
IEEE Abstract. IEEE Top Reference. BibRef
And:
Virtually Observable Temporal Kinematic Descriptors for Polynomial Translations,
DraftTracking vehicle motions (i.e. limited motions). BibRef

Santos-Victor, J., Sandini, G.,
Uncalibrated Obstacle Detection Using Normal Flow,
MVA(9), No. 3, 1996, pp. 130-137.
HTML Version. 9611 BibRef

Borenstein, J., Koren, Y.,
The Vector Field Histogram: Fast Obstacle Avoidance for Mobile Robots,
RA(7), 1991, pp. 278-288. BibRef 9100

Borenstein, J., Koren, Y.,
Histogramic In-Motion Mapping for Mobile Robot Obstacle Avoidance,
RA(7), 1991, pp. 535-539. BibRef 9100

Young, G.S., Herman, M., Hong, T.H., Jiang, D., Yang, J.C.S.,
New Visual Invariants for Terrain Navigation without 3D Reconstruction,
IJCV(28), No. 1, June 1998, pp. 45-71.
WWW Version. 9807 BibRef

Young, G.S., Hong, T.H., Herman, M., Yang, J.C.S.,
New Visual Invariants for Obstacle Detection Using Optical Flow Induced from General Motion,
WACV92(100-109).
IEEE Abstract. IEEE Top Reference. BibRef 9200

Vemuri, B.C., Chen, L., Vu-Quoc, L., Zhang, X., Walton, O.,
Efficient and Accurate Collision Detection for Granular Flow Simulation,
GMIP(60), No. 6, November 1998, pp. 403-422. BibRef 9811

Raviv, D.[Daniel], Joarder, K.[Kunal],
The Visual Looming Navigation Cue: A Unified Approach,
CVIU(79), No. 3, September 2000, pp. 331-363. 0008
WWW Version. BibRef
Earlier: A2, A1:
A Novel Method to Calculate Looming Cue for Threat of Collision,
SCV95(341-346).
IEEE Top Reference. BibRef
And: A2, A1:
A New Method to Calculate Looming for Autonomous Obstacle Avoidance,
CVPR94(777-780).
IEEE Abstract. IEEE Top Reference. Florida Atlantic University. Relative change in irradiance in the image to get the change in relative size. Study texture and change around the fixated point. BibRef

Gandhi, T., Devadiga, S., Kasturi, R., Camps, O.I.,
Detection of obstacles on runways using ego-motion compensation and tracking of significant features,
IVC(18), No. 10, July 2000, pp. 805-815.
WWW Version. 0005 BibRef
Earlier:
Detection of Obstacles on Runway Using Ego-Motion Compensation and Tracking of Significant Features,
WACV96(168-173).
IEEE Abstract. IEEE Top Reference. 9609 BibRef

Galbraith, J.M., Kenyon, G.T., Ziolkowski, R.W.,
Time-to-Collision Estimation from Motion Based on Primate Visual Processing,
PAMI(27), No. 8, August 2005, pp. 1279-1291.
IEEE Abstract. IEEE Top Reference. 0506Extract velocity features, similar to, but different from, optical flow. BibRef

Kimmerle, S.[Stefan], Nesme, M.[Matthieu], Faure, F.[Fran�ois],
Hierarchy Accelerated Stochastic Collision Detection,
VMV04(307-314). 0411 BibRef

Heinrich, S.,
Real Time Fusion of Motion and Stereo Using Flow/Depth Constraint for Fast Obstacle Detection,
DAGM02(75 ff.).
HTML Version. 0303 BibRef

Tistarelli, M., Guarnotta, F., Rizzieri, D., Tarocchi, F.,
Application of optical flow for automated overtaking control,
WACV94(105-112).
IEEE Abstract. IEEE Top Reference. 0403 BibRef