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Practical Aspect-Graph Derivation Incorporating Feature Segmentation Performance [chapter]

Andrew W. Fitzgibbon, Robert B. Fisher
1992 BMVC92  
A procedure is described for the automatic derivation of aspect graphs of surface-based geometric models. The object models are made of finite, typed, second order surface patches -allowing the representation of a large number of complex curved objects while retaining ease of recognition. A new representation, the detectability sphere, is developed to encode feature detectability constraints. The detectability metric is directly related to the performance of the imaging system, allowing the
more » ... m, allowing the generated aspect graph to more truthfully represent the scene's relationship with the vision system. An algorithm is described which fuses information from several views of the object to produce a small number of characteristic views which cover some desired portion of the viewsphere, and annotates these fundamental views with pose-verification hints. The procedure is compared with previous analytic and approximate solutions to the aspect-graph problem regarding relevance to the vision process, range of applicability, and computational complexity.
doi:10.1007/978-1-4471-3201-1_60 fatcat:pfnfnibjwnfptdcxl44yhn5q5i

Automatic 3D Model Construction for Turn-Table Sequences [chapter]

Andrew W. Fitzgibbon, Geoff Cross, Andrew Zisserman
1998 Lecture Notes in Computer Science  
Koch, Editors, Structure and Motion from Multiple Images in Large-Scale Environments, Lecture Notes in Computer Science, Springer 1998.158 Fitzgibbon, Cross and Zisserman 5 (1) In L.  ...  (b) Track lifetimes for dinosaur sequence: Each horizontal bar corresponds to a single point t r a c k, extending from the rst to last frame in which t h e p o i n t w as seen.  ... 
doi:10.1007/3-540-49437-5_11 fatcat:fyg6kvhhmrfxxd6trmtbht2lqe

Modelling human visual navigation using multi-view scene reconstruction

Lyndsey C. Pickup, Andrew W. Fitzgibbon, Andrew Glennerster
2013 Biological cybernetics  
N and w are free parameters in the model.  ...  along the xaxis (where here w = 40 cm), as shown in Fig. 3 .  ... 
doi:10.1007/s00422-013-0558-2 pmid:23778937 pmcid:PMC3755223 fatcat:egbf6a4xcvdyha4r2h7yenk6bi

Image-based environment matting

Yonatan Wexler, Andrew W. Fitzgibbon, Andrew Zisserman
2002 ACM SIGGRAPH 2002 conference abstracts and applications on - SIGGRAPH '02  
We return to this interpretation when computing W in section 5.  ...  Collecting the separate receptive fields for each (x, y) location yields the definition of the four-dimensional environment matte w(x, y, u, v) = r(u, v) at (x, y) Recovery of W is the primary goal of  ... 
doi:10.1145/1242073.1242211 dblp:conf/siggraph/WexlerFZ02 fatcat:v52wwjmfl5hdrj7cqrezdrrm6m

View-Based Approaches to Spatial Representation in Human Vision [chapter]

Andrew Glennerster, Miles E. Hansard, Andrew W. Fitzgibbon
2009 Lecture Notes in Computer Science  
We are grateful to Bruce Cumming, Andrew Parker and Hanspeter Mallot for helpful discussions.  ... 
doi:10.1007/978-3-642-03061-1_10 fatcat:7svhaetdtjd2jcp65kfkn7uxjm

Multibody Structure and Motion: 3-D Reconstruction of Independently Moving Objects [chapter]

Andrew W. Fitzgibbon, Andrew Zisserman
2000 Lecture Notes in Computer Science  
R h ¤ @ K E T W V I zd A K V v d s S { ¤ @ K E T W V | zd A W d d D } S { K V d ¤ g i B © k l k m B D y (5) where d} ¤ K T S V d s .  ...  Thus the error function for two objects has the form ¤ @ K V U ¹ s ¹ V B R V w ¹ s ¹ V B ¨V w ¹ s ¹ V Bd R V w ¹ s ¹ V Bd¨V w ¹ s ¹ V B £ V U ¹ s ¹ P E (10) ¤ a F µ VIEWS º » e 0 µ POINT INDICES ¶ p @  ... 
doi:10.1007/3-540-45054-8_58 fatcat:ou3jyzl5dvaslo6e66kfddhjdy

Fixation could simplify, not complicate, the interpretation of retinal flow

Andrew Glennerster, Miles E. Hansard, Andrew W. Fitzgibbon
2001 Vision Research  
The visual system must generate a reference frame to relate retinal images in spite of head and eye movements. We show how a reference frame for storing the visual direction and depth of points can be composed from the angles and changes in angles between pairs and triples of points. The representation has no unique origin in 3-D space nor a unique set of cardinal directions (basis vectors). We show how this relative representation could be built up over a series of fixations and for different
more » ... and for different directions of translation of the observer. Maintaining gaze on a point as the observer translates helps in building up this representation. In our model, retinal flow is divided into changes in eccentricity and changes in meridional angle. The latter, called 'polar angle disparities' for binocular viewing (Weinshall, 1990. Computer Vision Graphics and Image Processing, 49 222-241), can be used to recover the relief structure of the scene in a series of stages up to full Euclidean structure. We show how the direction of heading can be recovered by a similar series of stages.
doi:10.1016/s0042-6989(00)00300-x pmid:11248268 fatcat:ik4orzkaxjahfhpbjxaremcl7i

Reliable Fiducial Detection in Natural Scenes [chapter]

David Claus, Andrew W. Fitzgibbon
2004 Lecture Notes in Computer Science  
Reliable detection of fiducial targets in real-world images is addressed in this paper. We show that even the best existing schemes are fragile when exposed to other than laboratory imaging conditions, and introduce an approach which delivers significant improvements in reliability at moderate computational cost. The key to these improvements is in the use of machine learning techniques, which have recently shown impressive results for the general object detection problem, for example in face
more » ... r example in face detection. Although fiducial detection is an apparently simple special case, this paper shows why robustness to lighting, scale and foreshortening can be addressed within the machine learning framework with greater reliability than previous, more ad-hoc, fiducial detection schemes.
doi:10.1007/978-3-540-24673-2_38 fatcat:cmwjzn3uujf7dn7wjmyuzt2ldm

In Reply:

Kim W. Last, Ama Z.S. Rohatiner, Jude Fitzgibbon, T. Andrew Lister
2004 Journal of Clinical Oncology  
Kim W. Last Gastrointestinal Unit, Royal Marsden Hospita Ama Z.S. Rohatiner, Jude Fitzgibbon, and T.  ...  Andrew Lister CR-UK Medical Oncology Unit, St Bartholomew's Hospita United Kingdom Authors’ Disclosures of Potential Conflicts of Interest The authors indicated no potential conflicts of interest.  ... 
doi:10.1200/jco.2004.99.131 fatcat:4soxnu5ofvgo5czviikuupsohy

High-level cad model acquisition from range images

Andrew W Fitzgibbon, David W Eggert, Robert B Fisher
1997 Computer-Aided Design  
Automatic extraction of CAD descriptions which are ultimately intended for human manipulation requires the accurate inference of geometric and topological information. We present a system which applies segmentation techniques from computer vision to automatically extract CAD models from range images of parts with curved surfaces. The output of the system is a B-rep of the object which is suitable for further manipulation in a modelling system. The segmentation process is an improvement upon
more » ... mprovement upon Besl and Jain's variable-order surface tting 1 , extracting general quadric surfaces and planes from the data, with a postprocessing stage to identify surface intersections and to extract a B-rep from the segmented image. We present results on a variety of machined objects, which illustrate the high-level nature of the acquired models, and discuss the numerical accuracy (feature sizes and separations) and the correctness of structural inferences of the system.
doi:10.1016/s0010-4485(96)00059-0 fatcat:rkutyvqbp5bl7pdynb7h2mk4z4

Humans Ignore Motion and Stereo Cues in Favor of a Fictional Stable World

Andrew Glennerster, Lili Tcheang, Stuart J. Gilson, Andrew W. Fitzgibbon, Andrew J. Parker
2006 Current Biology  
P = 1=s 2 P 1=s 2 P + 1=s 2 T ; w T = 1=s 2 T 1=s 2 P + 1=s 2 T (2) Substituting the average values ofP,T, andR given above into equation 1 and rearranging gives the predicted size match: R = 1 w P + w  ...  the Bayesian prior is uniform (all values of R between 1 and 4 are equally likely a priori), then the maximum-likelihood estimate [12, 13] of the size match is given by:R =Pw P +Tw T = 1 (1) where w  ... 
doi:10.1016/j.cub.2006.01.019 pmid:16488879 pmcid:PMC2833396 fatcat:7yhfdalvknalpfv2eke77juul4

Spatial calibration of an optical see-through head-mounted display

Stuart J. Gilson, Andrew W. Fitzgibbon, Andrew Glennerster
2008 Journal of Neuroscience Methods  
We present here a method for calibrating an optical see-through Head Mounted Display (HMD) using techniques usually applied to camera calibration (photogrammetry). Using a camera placed inside the HMD to take pictures simultaneously of a tracked object and features in the HMD display, we could exploit established camera calibration techniques to recover both the intrinsic and extrinsic properties of the HMD (width, height, focal length, optic centre and principal ray of the display). Our method
more » ... isplay). Our method gives low re-projection errors and, unlike existing methods, involves no time-consuming and error-prone human measurements, nor any prior estimates about the HMD geometry.
doi:10.1016/j.jneumeth.2008.05.015 pmid:18599125 pmcid:PMC2816817 fatcat:yjtqn5fzhvax5lbrpzwsdtkufe

Bundle Adjustment — A Modern Synthesis [chapter]

Bill Triggs, Philip F. McLauchlan, Richard I. Hartley, Andrew W. Fitzgibbon
2000 Lecture Notes in Computer Science  
Fitzgibbon). We would like to thank A. Zisserman, A. Grün and W. Förstner for valuable comments and references. A version of this paper will appear in Vision Algorithms: Theory & Practice, B.  ...  H −1 ∓ J i W i W i ± W i J i H −1 ∓ J i W i −1 W i J i H −1 ∓ = α H −1 − − H −1 + (44) ≈ α H −1 ± J i W −1 i J i H −1 ± (45) so, e.g., δx H ± δx ≤ α Trace J i H −1 ± J i W −1 i and U δx 2 ≤ α Trace J i  ...  The normal equations are the resulting Gauss-Newton step prediction equations (J W J) δx = −(J W z). Gauss-Seidel method: See alternation.  ... 
doi:10.1007/3-540-44480-7_21 fatcat:jm2ewshh5bejhnv5dixghvp6y4

An automated calibration method for non-see-through head mounted displays

Stuart J. Gilson, Andrew W. Fitzgibbon, Andrew Glennerster
2011 Journal of Neuroscience Methods  
− c x f x , bottom = −ncp × c y f y , top = ncp × h − c y f y define the borders of the frustum's near clipping plane (w and h are the pixel width and the height of the graphics viewport, and ncp and fcp  ...  The cost function was the reprojection error -that is, the root-mean-square (RMS) difference (in pixels) between the original projections x HMD and the new projections computed by: (x t , y t , z t , w  ... 
doi:10.1016/j.jneumeth.2011.05.011 pmid:21620891 pmcid:PMC3142613 fatcat:4sddsdcf4rgjxotmgtrfijd5ni

Robust registration of 2D and 3D point sets

Andrew W Fitzgibbon
2003 Image and Vision Computing  
I would like to thank David Capel, Frederik Schaffalitzky and Andrew Zisserman for discussions relating to this work, and the Royal Society for its generous funding.  ... 
doi:10.1016/j.imavis.2003.09.004 fatcat:m6vmwuqxkras3ldz7sw2xgp54i
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