Results 1  10
of
18
Automatic camera recovery for closed or open image sequences.
 In European conference on computer vision
, 1998
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3D Model Acquisition from Extended Image Sequences
, 1995
"... This paper describes the extraction of 3D geometrical data from image sequences, for the purpose of creating 3D models of objects in the world. The approach is uncalibrated  camera internal parameters and camera motion are not known or required. Processing an image sequence is underpinned by token ..."
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Cited by 236 (29 self)
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This paper describes the extraction of 3D geometrical data from image sequences, for the purpose of creating 3D models of objects in the world. The approach is uncalibrated  camera internal parameters and camera motion are not known or required. Processing an image sequence is underpinned by token correspondences between images. We utilise matching techniques which are both robust (detecting and discarding mismatches) and fully automatic. The matched tokens are used to compute 3D structure, which is initialised as it appears and then recursively updated over time. We describe a novel robust estimator of the trifocal tensor, based on a minimum number of token correspondences across an image triplet; and a novel tracking algorithm in which corners and line segments are matched over image triplets in an integrated framework. Experimental results are provided for a variety of scenes, including outdoor scenes taken with a handheld camcorder. Quantitative statistics are included to asses...
Sequential updating of projective and affine structure from motion
 International Journal of Computer Vision
, 1997
"... A structure from motion algorithm is described which recovers structure and camera position, modulo a projective ambiguity. Camera calibration is not required, and camera parameters such as focal length can be altered freely during motion. The structure is updated sequentially over an image sequenc ..."
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Cited by 161 (4 self)
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A structure from motion algorithm is described which recovers structure and camera position, modulo a projective ambiguity. Camera calibration is not required, and camera parameters such as focal length can be altered freely during motion. The structure is updated sequentially over an image sequence, in contrast to schemes which employ a batch process. A specialisation of the algorithm to recover structure and camera position modulo an affine transformation is described, together with a method to periodically update the affine coordinate frame to prevent drift over time. We describe the constraint used to obtain this specialisation. Structure is recovered from image corners detected and matched automatically and reliably in real image sequences. Results are shown for reference objects and indoor environments, and accuracy of recovered structure is fully evaluated and compared for a number of reconstruction schemes. A specific application of the work is demonstrated  affine structure is used to compute free space maps enabling navigation through unstructured environments and avoidance of obstacles. The path planning involves only affine constructions.
Graph Matching With a DualStep EM Algorithm
 IEEE Transactions on Pattern Analysis and Machine Intelligence
, 1998
"... Abstract—This paper describes a new approach to matching geometric structure in 2D pointsets. The novel feature is to unify the tasks of estimating transformation geometry and identifying pointcorrespondence matches. Unification is realized by constructing a mixture model over the bipartite graph ..."
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Cited by 104 (6 self)
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Abstract—This paper describes a new approach to matching geometric structure in 2D pointsets. The novel feature is to unify the tasks of estimating transformation geometry and identifying pointcorrespondence matches. Unification is realized by constructing a mixture model over the bipartite graph representing the correspondence match and by affecting optimization using the EM algorithm. According to our EM framework, the probabilities of structural correspondence gate contributions to the expected likelihood function used to estimate maximum likelihood transformation parameters. These gating probabilities measure the consistency of the matched neighborhoods in the graphs. The recovery of transformational geometry and hard correspondence matches are interleaved and are realized by applying coupled update operations to the expected loglikelihood function. In this way, the two processes bootstrap one another. This provides a means of rejecting structural outliers. We evaluate the technique on two realworld problems. The first involves the matching of different perspective views of 3.5inch floppy discs. The second example is furnished by the matching of a digital map against aerial images that are subject to severe barrel distortion due to a linescan sampling process. We complement these experiments with a sensitivity study based on synthetic data.
Metric calibration of a stereo rig
 In Proc. IEEE Workshop on Representation of Visual Scenes
, 1995
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The problem of degeneracy in structure and motion recovery from uncalibrated image sequences
 International Journal of Computer Vision
, 1999
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Impsac: A synthesis of importance sampling and random sample consensus to effect multiscale image matching for small and wide baselines
 In ECCV2000
, 2000
"... The goal of this work is to obtain accurate matches and epipolar geometry between two images of the same scene, where the motion is unlikely to be smooth or known a priori. Once the matches and two view image relation have been recovered, they can be used for image compression, for building 3D model ..."
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Cited by 58 (1 self)
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The goal of this work is to obtain accurate matches and epipolar geometry between two images of the same scene, where the motion is unlikely to be smooth or known a priori. Once the matches and two view image relation have been recovered, they can be used for image compression, for building 3D models [3, 33, 35, 48], for object recognition [19], for extraction of images from databases [31]
Automatic 3d model acquisition and generation of new images from video sequences.
 In Proceedings of European Signal Processing Conference,
, 1998
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Active visual navigation using nonmetric structure.
 In Proceedings of the 5th International Conference on Computer Vision,
, 1995
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Robust detection of degenerate configurations while estimating the fundamental matrix
 Computer Vision and Image Understanding
, 1998
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