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Learning methods for generic object recognition with invariance to pose and lighting

Learning methods for generic object recognition with invaria...

引用

Proceedings of the 2004 ieee computer society conference on computer vision and pattern recognition, cvpr 2004

作者： LeCun, Yann Huang, Fu Jie Bottou, Léon Courant Institute New York University 715 Broadway New York NY 10003 United States NEC Labs. America 4 Independence Way Princeton NJ 08540

We assess the applicability of several popular learning methods for the problem of recognizing generic visual categories with invariance to pose, lighting, and surrounding clutter. A large dataset comprising stereo image pairs of 50 uniform-colored toys under 36 azimuths, 9 elevations, and 6 lighting conditions was collected (for a total of 194,400 individual images). The objects were 10 instances of 5 generic categories: four-legged animals, human figures, airplanes, trucks, and cars. Five instances of each category were used for training, and the other five for testing. Low-resolution grayscale images of the objects with various amounts of variability and surrounding clutter were used for training and testing. Nearest Neighbor methods, Support Vector Machines, and Convolutional Networks, operating on raw pixels or on PCA-derived features were tested. Test error rates for unseen object instances placed on uniform backgrounds were around 13% for SVM and 7% for Convolutional Nets. On a segmentation/recognition task with highly cluttered images, SVM proved impractical, while Convolutional nets yielded 16/7% error. A real-time version of the system was implemented that can detect and classify objects in natural scenes at around 10 frames per second.

关键词： Object recognition

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3D human limb detection using space carving and multi-view eigen models

3D human limb detection using space carving and multi-view e...

引用

2004 ieee computer society conference on computer vision and pattern recognition Workshops, cvprW 2004

作者： Bhatia, Sidharth Sigal, Leonid Isard, Michael Black, Michael J. Department of Computer Science Brown University Providence RI02912 United States Microsoft Research Silicon Valley Mountain ViewCA94043 United States

In this paper, we integrate space carving and eigen detection methods to develop a bottom-up 3D human limb detector. We model the body in terms of its constituent body parts;here we focus on the head, lower arms, upper arms and calves. For each body part, we build a multi-view eigen model that combines image views from multiple calibrated cameras. This approach is much more constraining than the conventional multiple single-view eigen models and provides coarse 3D pose information. We use ideas from space carving using multiple silhouette images to constrain the volume of our search for the body part locations. We have applied the method to detect the body parts of a subject in long test sequences. The approach provides bottom-up in-formation that supports the automatic initialization of a full 3D human body model. © 2004 ieee.

关键词： computer vision

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Automatic single view building reconstruction by integrating segmentation

Automatic single view building reconstruction by integrating...

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2004 ieee computer society conference on computer vision and pattern recognition Workshops, cvprW 2004

作者： Han, Feng Zhu, Song-Chun Departments of Computer Science and Statistics University of California Los Angeles Los AngelesCA90095 United States

In this paper, we propose a stochastic algorithm using Markov chain Monte Carlo (MCMC) to automatically reconstruct buildings from a single image of architectural scenes by integrating segmentation and reconstruction. Buildings are modelled by two families of generative models: One is parameterized geometric primitives (e.g. boxes, prisms) for 3D structures of buildings. The other is image models for appearances of building surfaces. All the other objects except buildings in the scene are modelled as a 3D background plane with some appearance. Regarding one image of architectural scenes as the 2D projection of the appearances of all the component primitives in the buildings and the background plane to the image plane, we reconstruct buildings under the Bayesian statistical framework by inferring the 3D structure of its component primitives and image models of visible surfaces, which follow some spatial relation prior and reproduce the given image under some projection matrix. The aspect hierarchy is used to generate proposals in primitive space, which can greatly speed up the Markov chain search. © 2004 ieee.

关键词： Buildings

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The world in an eye

The world in an eye

引用

Proceedings of the 2004 ieee computer society conference on computer vision and pattern recognition, cvpr 2004

作者： Nishino, Ko Nayar, Shree K. Department of Computer Science Columbia University New York NY 10027

This paper provides a comprehensive analysis of exactly what visual information about the world is embedded within a single image of an eye. It turns out that the cornea of an eye and a camera viewing the eye form a catadioptric imaging system. We refer to this as a corneal imaging system. Unlike a typical catadioptric system, a corneal one is flexible in that the reflector (cornea) is not rigidly attached to the camera. Using a geometric model of the cornea based on anatomical studies, its 3D location and orientation can be estimated from a single image of the eye. Once this is done, a wide-angle view of the environment of the person can be obtained from the image. In addition, we can compute the projection of the environment onto the retina with its center aligned with the gaze direction. This foveated retinal image reveals what the person is looking at. We present a detailed analysis of the characteristics of the corneal imaging system including field of view, resolution and locus of viewpoints. When both eyes of a person are captured in an image, we have a stereo corneal imaging system. We analyze the epipolar geometry of this stereo system and show how it can be used to compute 3D structure. The framework we present in this paper for interpreting eye images is passive and non-invasive. It has direct implications for several fields including visual recognition, human-machine interfaces, computer graphics and human affect studies.

关键词： Imaging systems

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Jitter camera: High resolution video from a low resolution detector

Jitter camera: High resolution video from a low resolution d...

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Proceedings of the 2004 ieee computer society conference on computer vision and pattern recognition, cvpr 2004

作者： Ben-Ezra, Moshe Zomet, Assaf Nayar, Shree K. Computer Science Department Columbia University New York NY 10027

Video cameras must produce images at a reasonable frame-rate and with a reasonable depth of field. These requirements impose fundamental physical limits on the spatial resolution of the image detector. As a result, current cameras produce videos with a very low resolution. The resolution of videos can be computationally enhanced by moving the camera and applying super-resolution reconstruction algorithms. However, a moving camera introduces motion blur, which limits super-resolution quality. We analyze this effect and derive a theoretical result showing that motion blur has a substantial degrading effect on the performance of super resolution. The conclusion is, that in order to achieve the highest resolution, motion blur should be avoided. Motion blur can be minimized by sampling the space-time volume of the video in a specific manner. We have developed a novel camera, called the "jitter camera," that achieves this sampling. By applying an adaptive super-resolution algorithm to the video produced by the jitter camera, we show that resolution can be notably enhanced for stationary or slowly moving objects, while it is improved slightly or left unchanged for objects with fast and complex motions. The end result is a video that has a significantly higher resolution than the captured one.

关键词： Cameras

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Error analysis for a navigation algorithm based on optical-flow and a digital terrain map

Error analysis for a navigation algorithm based on optical-f...

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Proceedings of the 2004 ieee computer society conference on computer vision and pattern recognition, cvpr 2004

作者： Lerner, R. Rivlin, E. Rotstein, P.H. Dept. of Computer Science Technion Haifa 32000 Israel Dept. of Aerospace Engineering University of Minnesota Minneapolis MN 55455

This paper deals with the error analysis of a novel navigation algorithm that uses as input the sequence of images acquired from a moving camera and a Digital Terrain (or Elevation) Map (DIM/DEM). More specifically, it has been shown that the optical flow derived from two consecutive camera frames can be used in combination with a DTM to estimate the position, orientation and ego-motion parameters of the moving camera. As opposed to previous works, the proposed approach does not require an intermediate explicit reconstruction of the 3D world. In the present work the sensitivity of the algorithm outlined above is studied. The main sources for errors are identified to be the optical-flow evaluation and computation, the quality of the information about the terrain, the structure of the observed terrain and the trajectory of the camera. By assuming appropriate characterization of these error sources, a closed form expression for the uncertainty of the pose and motion of the camera is first developed and then the influence of these factors is confirmed using extensive numerical simulations. The main conclusion of this paper is to establish mat the proposed navigation algorithm generates accurate estimates for reasonable scenarios and error sources, and thus can be effectively used as part of a navigation system of autonomous vehicles.

关键词： Image processing

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Integrating algebraic functions of views with indexing and learning for 3D object recognition

Integrating algebraic functions of views with indexing and l...

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2004 ieee computer society conference on computer vision and pattern recognition Workshops, cvprW 2004

作者： Li, Wenjing Bebis, George Bourbakis, Nikolaos Computer Vision Laboratory University of Nevada Reno United States Information Technology Research Institute Wright State University United States

This paper focuses on the problem of 3D object recognition from different viewing angles and positions. In particular, we propose a new approach that integrates Algebraic Functions of Views (AFoVs) with indexing and learning. During training, we consider groups of point features and we represent a sparse number of views that they can produce in a k-d tree. Moreover, we learn the manifold formed by a dense number of views using mixture models and Expectation-Maximization (EM). Learning takes place in a "universal", lower-dimensional, space computed through Random Projection (RP). The images that a group of model points can produce are computed off-line using AFoVs by combining a small number of reference views that contain the group. Rigidity constraints are imposed during this step to remove unrealistic views. During recognition, groups of point features are extracted from the scene and used to retrieve from the k-d tree the most feasible model groups that might have produced them. To reduce the number of hypotheses for verification, we rank them by computing the probability that the hypothesized model group is present in the scene. Only hypotheses ranked high enough are considered for further verification. The proposed method has been evaluated using both artifical and real data, illustrating good performance. © 2004 ieee.

关键词： Object recognition

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Tracking loose-limbed people

Tracking loose-limbed people

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Proceedings of the 2004 ieee computer society conference on computer vision and pattern recognition, cvpr 2004

作者： Sigal, Leonid Bhatia, Sidharth Roth, Stefan Black, Michael J. Isard, Michael Department of Computer Science Brown University Providence RI 02912 Microsoft Research Silicon Valley Mountain View CA 94043

We pose the problem of 3D human tracking as one of inference in a graphical model. Unlike traditional kinematic tree representations, our model of the body is a collection of loosely-connected limbs. Conditional probabilities relating the 3D pose of connected limbs are learned from motion-captured training data. Similarly, we learn probabilistic models for the temporal evolution of each limb (forward and backward in time). Human pose and motion estimation is then solved with non-parametric belief propagation using a variation of particle filtering that can be applied over a general loopy graph. The loose-limbed model and decentralized graph structure facilitate the use of low-level visual cues. We adopt simple limb and head detectors to provide "bottom-up" information that is incorporated into the inference process at every time-step;these detectors permit automatic initialization and aid recovery from transient tracking failures. We illustrate the method by automatically tracking a walking person in video imagery using four calibrated cameras. Our experimental apparatus includes a marker-based motion capture system aligned with the coordinate frame of the calibrated cameras with which we quantitatively evaluate the accuracy of our 3D person tracker.

关键词： Object recognition

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Face recognition in the thermal infrared spectrum

Face recognition in the thermal infrared spectrum

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2004 ieee computer society conference on computer vision and pattern recognition Workshops, cvprW 2004

作者： Buddharaju, Pradeep Pavlidis, Ioannis Kakadiaris, Ioannis Computer Science Department University of Houston HoustonTX77204-3010 United States

We present a two-stage face recognition method based on infrared imaging and statistical modeling. In the first stage we reduce the search space by finding highly likely candidates before arriving at a singular conclusion during the second stage. Previous work has shown that Bessel forms model accurately the marginal densities of filtered components and can be used to find likely matches but not a unique solution. We present an enhancement to this approach by applying Bessel modeling on the facial region only rather than the entire image and by pipelining a classification algorithm to produce a unique solution. The detailed steps of our method are as follows: First, the faces are separated from the background using adaptive fuzzy connectedness segmentation. Second, Gabor filtering is used as a spectral analysis tool. Third, the derivative filtered images are modeled using two-parameter Bessel forms. Fourth, high probability subjects are short-listed by applying the L^2 -norm on the Bessel models. Finally, the resulting set of highly likely matches is fed to a Bayesian classifier to find the exact match. We show experimentally that segmentation of the facial regions results in better hypothesis pruning and classification performance. We also present comparative experimental results with an eigenface approach to highlight the potential of our method. © 2004 ieee.

关键词： Face recognition

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Eye typing off the shelf

Eye typing off the shelf

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Proceedings of the 2004 ieee computer society conference on computer vision and pattern recognition, cvpr 2004

作者： Hansen, Dan Witzner Pece, Arthur Dept. of Innovation IT University Copenhagen Copenhagen Denmark Heimdall Vision Dept. of Computer Science University of Copenhagen Copenhagen Denmark

The goal of this work is using off-the-shelf components for gaze-based interaction, with focus on eye typing. Avoiding the use of dedicated hardware such as IR light emitters makes eye tracking significantly more difficult and requires robust methods capable of handling large changes in image quality. We employ an active-contour method to obtain robust iris tracking. The main strength of the method is that the contour model avoids explicit feature detection: contours are simply assumed to remove statistical dependencies on opposite sides of the contour. The contour model is utilized in an approach combining particle filtering with the EM algorithm. The method is robust against light changes and camera defocusing. For the purpose of determining where the user is looking calibrations is usually needed. The number of calibration points used in different methods varies from from a few to several thousands, depending on the prior knowledge used on the setup and equipment. We examine basic properties of gaze determination when the geometry of the the camera, screen and user is unknown. In particular we present a lower bound on the number of calibration points needed for gaze determination on planar objects, and we examine degenerate configurations. Based on this lower bound we apply a simple calibration procedure, to facilitate button selections for fast on-screen typing.

关键词： Image analysis

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