Constructing virtual worlds using dense stereo

Narayanan, P. J.; Rander, Peter; Kanade, Takeo

doi:10.1109/iccv.1998.710694

Cited by 195 publications

(126 citation statements)

References 22 publications

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“…Intermediate rotations can be normalized by using an eight-parameter planar model to warp images to match with the initial frame (Black & Yacoob, 1985;Wu, Kanade, Cohn, & Li, 1998). For larger rotations, however, higher-degree motion models or multiple-camera setups may be needed (Basu, Essa, & Pentland, 1996;DeCarlo & Metaxis, 1995;Narayanan, Rander, & Kanade, 1998;Vetter, 1995). Multiple camera setups already are common in observational research, so the necessary recording capability is present in many laboratories.…”

Section: Action Units In the Brow Regionmentioning

confidence: 99%

Automated Face Analysis by Feature Point Tracking Has High Concurrent Validity With Manual FACS Coding

Cohn¹,

Zlochower²,

Lien³

et al. 2005

What the Face RevealsBasic and Applied Studies of Spontaneous Expression Using the Facial Action Coding System (FACS)

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The face is a rich source of information about human behavior. Available methods for coding facial displays, however, are human-observer dependent, labor intensive, and difficult to standardize. To enable rigorous and efficient quantitative measurement of facial displays, we have developed an automated method of facial display analysis. In this report we compare the results with those of manual FACS (Facial Action Coding System, Ekman & Friesen, 1978a) coding. One hundred university students were videotaped while performing a series of facial displays. The image sequences were coded from videotape by certified FACS coders. Fifteen action units and action unit combinations that occurred a minimum of 25 times were selected for automated analysis. Facial features were automatically tracked in digitized image sequences using a hierarchical algorithm for estimating optical flow. The measurements were normalized for variation in position, orientation, and scale. The image sequences were randomly divided into a training set and a cross-validation set, and discriminant function analyses were conducted on the feature point measurements. In the training set, average agreement with manual FACS coding was 92% or higher for action units in the brow, eye, and mouth regions. In the crossvalidation set, average agreement was 91%, 88%, and 81% for action units in the brow, eye, and mouth regions, respectively. Automated Face Analysis by feature point tracking demonstrated high concurrent validity with manual FACS coding.

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Section: Action Units In the Brow Regionmentioning

confidence: 99%

Automated Face Analysis by Feature Point Tracking Has High Concurrent Validity With Manual FACS Coding

Cohn¹,

Zlochower²,

Lien³

et al. 2005

What the Face RevealsBasic and Applied Studies of Spontaneous Expression Using the Facial Action Coding System (FACS)

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“…From our point of view, the most impressive demonstration of dense depth map computation comes from the group of Kanade at the Robotics Institute, Carnegie Mellon Univ. Starting with their seminal work [152], Prof. Kanade and his students have now been able to produce dense depth maps in real-time thanks to a video-rate stereo machine developed at the expense of large computational power [113,149,204]. There exist many more modest systems that provide acceptable results, including the ones by Aranda [15] or Konolige [117], and our own laboratory version [144].…”

Section: Low-level Processing Of 2d Intensity Imagesmentioning

confidence: 99%

Environment Learning for Indoor Mobile Robots

Andrade‐Cetto¹

2006

Springer Tracts in Advanced Robotics

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This thesis focuses on the various aspects of autonomous environment learning for indoor service robots. Particularly, on landmark extraction from sensor data, autonomous map building, and robot localization.To univocally identify landmarks from sensor data, we study several landmark representations, and the mathematical foundation necessary to extract the features that build them from images and laser range data. The features extracted from just one sensor may not suffice in the invariant characterization of landmarks and objects, pushing for the combination of information from multiple sources. We present a new algorithm that fuses complementary information from two low level vision modules into coherent object models that can be tracked and learned in a mobile robotics context. Illumination conditions and occlusions are the most prominent artifacts that hinder data association in computer vision. By using photogrammetric and geometric constraints we restrict the search for landmark matches in successive images, and by locking our interest in one or a set of landmarks in the scene, we track those landmarks along successive frames, reducing considerably the data association problem. We concentrate on those tools from the geometry of multiple views that are relevant to the computation of initial landmark location estimates for coarse motion recovery; a desirable characteristic when odometry is not available or is highly unreliable.Once landmarks are accurately extracted and identified, the second part of the problem is to use these observations for the localization of the robot, as well as the refinement of the landmark location estimates. We consider robot motion and sensor observations as stochastic processes, and treat the problem from an estimation theoretic point of view, dealing with noise by using probabilistic methods.The main drawback we encounter is that current estimation techniques have been devised for static environments, and that they lack robustness in more realistic situations. To aid in those situations in which landmark observations might not be consistent in time, we propose a new set of temporal landmark quality functions, and show how iii by incorporating these functions in the data association tests, the overall estimationtheoretic approach to map building and localization is improved. The basic idea consists on using the history of data association mismatches for the computation of the likelihood of future data association, together with the spatial compatibility tests already available.Special attention is paid in that the removal of spurious landmarks from the map does not violate the basic convergence properties of the localization and map building algorithms already described in the literature; namely, asymptotic convergence and full correlation.The thesis also gives an in depth analysis of the fully correlated model to localization and map building from a control systems theory point of view. Considering the fact that the Kalman filter is nothing else but an optimal observer,...

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“…Though the explosion of Internet has produced many systems claiming tele-presence, none of them is working towards the scale necessary for tele-immersion. The closest to the proposed work is CMU's Virtualized Reality [7] and its early dedicated real-time parallel architecture for stereo. Other multi-camera systems include the view-dependent visual hull approach [5], the Keck laboratory at the University of Maryland [1] and the Argus system at Duke University [2].…”

Section: Related Workmentioning

confidence: 99%

Real-time Terascale Implementation of Tele-immersion

Kelshikar

Zabulis

Mulligan

et al. 2003

Lecture Notes in Computer Science

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Abstract. Tele-immersion is a new medium that enables a user to share a virtual space with remote participants, by creating the illusion that users at geographically dispersed locations reside at the same physical space. A person is immersed in a remote world, whose 3D representation is acquired remotely, then transmitted and displayed in the viewer's environment. Tele-immersion is effective only when the three components, computation, transmission, and rendering -all operate in real time . In this paper, we describe the real-time implementation of scene reconstruction on the Terascale Computing System at the Pittsburgh Supercomputing Center.

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Constructing virtual worlds using dense stereo

Cited by 195 publications

References 22 publications

Automated Face Analysis by Feature Point Tracking Has High Concurrent Validity With Manual FACS Coding

Automated Face Analysis by Feature Point Tracking Has High Concurrent Validity With Manual FACS Coding

Environment Learning for Indoor Mobile Robots

Real-time Terascale Implementation of Tele-immersion

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