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Multi-Target Tracking - Linking Identities using Bayesian Network Inference

Multi-Target Tracking - Linking Identities using Bayesian Ne...

引用

conference on computer vision and pattern recognition (CVPR)

作者： P. Nillius J. Sullivan S. Carlsson Institute of Computer Science FORTH Heraklion Greece School of Computer Science & Communication Royal Institute of Technology Stockholm Sweden

Multi-target tracking requires locating the targets and labeling their identities. The latter is a challenge when many targets, with indistinct appearances, frequently occlude one another, as in football and surveillance tracking. We present an approach to solving this labeling problem. When isolated, a target can be tracked and its identity maintained. While, if targets interact this is not always the case. This paper assumes a track graph exists, denoting when targets are isolated and describing how they interact. Measures of similarity between isolated tracks are defined. The goal is to associate the identities of the isolated tracks, by exploiting the graph constraints and similarity measures. We formulate this as a Bayesian network inference problem, allowing us to use standard message propagation to find the most probable set of paths in an efficient way. The high complexity inevitable in large problems is gracefully reduced by removing dependency links between tracks. We apply the method to a 10 min sequence of an international football game and compare results to ground truth.

关键词： Joining processes Bayesian methods Target tracking computer science Labeling Robustness Filtering Surveillance Information resources Information analysis

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Multi-Resolution Spin-Images

Multi-Resolution Spin-Images

引用

conference on computer vision and pattern recognition (CVPR)

作者： H.Q. Dinh S. Kropac Department of Computer Science Stevens Institute of Technology USA

Johnson and Hebert’s spin-images have been applied to the registration of range images and object recognition with much success because they are rotation, scale, and pose invariant. In this paper we address two issues concerning spin-images, namely: (1) comparing uncompressed spinimages across large datasets is costly, and (2) a method to select the appropriate bin size and image width for spinimages is not clearly defined. Our solution to these issues is a multi-resolution method that generates a pyramid of spin-images by successively decreasing the spin-image size by powers of two. To efficiently correlate surface points, we compare spin-images in a low-to-high resolution manner. Once multi-resolution spin-images are generated for a given object, we have found that the different resolutions can also be used to compare objects that have differing or non-uniform point densities. To select the appropriate bin sizes for comparing such objects, we use the ratio of the average edge lengths of the objects. We also show preliminary results of using the pyramid to converge on the appropriate image width by traversing the pyramid in a low-to-high resolution manner looking for the highest resolution at which the fewest number of highly correlated points are found to match a given feature point.

关键词： Image resolution Multiresolution analysis computer science Image converters Shape measurement Object recognition Power generation Spline Image sampling Timing

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Joint recognition of Complex Events and Track Matching

Joint Recognition of Complex Events and Track Matching

引用

conference on computer vision and pattern recognition (CVPR)

作者： M.T. Chan A. Hoogs R. Bhotika A. Perera J. Schmiederer G. Doretto One Research Circle GE Global Research Center Niskayuna NY USA

We present a novel method for jointly performing recognition of complex events and linking fragmented tracks into coherent, long-duration tracks. Many event recognition methods require highly accurate tracking, and may fail when tracks corresponding to event actors are fragmented or partially missing. However, these conditions occur frequently from occlusions, traffic and tracking errors. Recently, methods have been proposed for linking track fragments from multiple objects under these difficult conditions. Here, we develop a method for solving these two problems jointly. A hypothesized event model, represented as a Dynamic Bayes Net, supplies data-driven constraints on the likelihood of proposed track fragment matches. These event-guided constraints are combined with appearance and kinematic constraints used in the previous track linking formulation. The result is the most likely track linking solution given the event model, and the highest event score given all of the track fragments. The event model with the highest score is determined to have occurred, if the score exceeds a threshold. Results demonstrated on a busy scene of airplane servicing activities, where many non-event movers and long fragmented tracks are present, show the promise of the approach to solving the joint problem.

关键词： Layout Joining processes Airplanes Traffic control Kinematics Robustness Bayesian methods Spatiotemporal phenomena Position measurement computer society

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Multi-Scale Contour Extraction Based on Natural Image Statistics

Multi-Scale Contour Extraction Based on Natural Image Statis...

引用

ieee computer society conference on computer vision and pattern recognition Workshops (CVPRW)

作者： F.J. Estrada J.H. Elder Centre for Vision Research York University Toronto ONT Canada

Perceptual grouping of the complete boundaries of objects in natural images remains an unsolved problem in computer vision. The computational complexity of the problem and difficulties capturing global constraints limit the performance of current algorithms. In this paper we develop a coarse-to-fine Bayesian algorithm which addresses these constraints. Candidate contours are extracted at a coarse scale and then used to generate spatial priors on the location of possible contours at finer scales. In this way, a rough estimate of the shape of an object is progressively refined. The coarse estimate provides robustness to texture and clutter while the refinement process allows for the extraction of detailed object contours. The grouping algorithm is probabilistic and uses multiple grouping cues derived from natural scene statistics. We present a quantitative evaluation of grouping performance on the Berkeley Segmentation Database, and show that the multi-scale approach outperforms several single-scale contour extraction algorithms.

关键词： Statistics Shape Layout computer vision Image segmentation Image databases Computational complexity Bayesian methods Robustness Data mining

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3D Surface Matching and recognition Using Conformal Geometry

3D Surface Matching and Recognition Using Conformal Geometry

引用

conference on computer vision and pattern recognition (CVPR)

作者： Sen Wang Yang Wang Miao Jin Xianfeng Gu D. Samaras Computer Science Department State University of New York Stony Brook Stony Brook NY USA

3D surface matching is a fundamental issue in computer vision with many applications such as shape registration, 3D object recognition and classification. However, surface matching with noise, occlusion and clutter is a challenging problem. In this paper, we analyze a family of conformal geometric maps including harmonic maps, conformal maps and least squares conformal maps with regards to 3D surface matching. As a result, we propose a novel and computationally efficient surface matching framework that uses least squares conformal maps. According to conformal geometry theory, each 3D surface with disk topology can be mapped to a 2D domain through a global optimization and the resulting map is a diffeomorphism, i.e., one-to-one and onto. This allows us to simplify the 3D surface-matching problem to a 2D image-matching problem, by comparing the resulting 2D conformal geometric maps, which are stable, insensitive to resolution changes and robust to occlusion and noise. Therefore, highly accurate and efficient 3D surface matching algorithms can be achieved by using conformal geometric maps. Finally, the performance of conformal geometric maps is evaluated and analyzed comprehensively in 3D surface matching with occlusion, noise and resolution variation. We also provide a series of experiments on real 3D face data that achieve high recognition rates.

关键词： Least squares methods Computational geometry computer vision Application software Shape Object recognition Noise shaping Harmonic analysis Topology Image resolution

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Beyond RANSAC: User Independent Robust Regression

Beyond RANSAC: User Independent Robust Regression

引用

ieee computer society conference on computer vision and pattern recognition Workshops (CVPRW)

作者： R. Subbarao P. Meer Department of Electrical and Computer Engineering Rutgers University Piscataway NJ USA

RANSAC is the most widely used robust regression algorithm in computer vision. However, RANSAC has a few drawbacks which make it difficult to use in a lot of applications. Some of these problems have been addressed through improved sampling algorithms or better cost functions, but an important problem still remains. The algorithms are not user independent, and require some knowledge of the scale of the inlier noise. The projection based M-estimator (pbM) offers a solution to this by reframing the regression problem in a projection pursuit framework. In this paper we derive the pbM algorithm for heteroscedastic data. Our algorithm is applied to various real problems and its performance is compared with RANSAC and MSAC. It is shown that pbM gives better results than RANSAC and MSAC in spite of being user independent.

关键词： computer vision Application software Sampling methods Motion estimation Parameter estimation Cost function Interference Noise robustness Project management Kernel

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Multispectral Iris Analysis: A Preliminary Study51

Multispectral Iris Analysis: A Preliminary Study51

引用

ieee computer society conference on computer vision and pattern recognition Workshops (CVPRW)

作者： C. Boyce A. Ross M. Monaco L. Hornak Xin Li Lane Department of Computer Science and Electrical Engineering West Virginia University Morgantown WV USA

This paper explores the possibility of using multispectral iris information to enhance the recognition performance of an iris biometric system. Commercial iris recognition systems typically sense the iridal reflection pertaining to the near-infrared (IR) range of the electromagnetic spectrum. This work examines the iris information represented in the visible and IR portion of the spectrum. It is hypothesized that, based on the color of the eye, different components of the iris are highlighted at multiple wavelengths. To this end, an acquisition procedure for obtaining co-registered multispectral iris images associated with the IR, Red, Green and Blue wavelengths of the electromagnetic spectrum, is first discussed. The components of the iris that are revealed in multiple spectral channels/wavelengths based on the color of the eye are studied. An adaptive histogram equalization scheme is invoked to enhance the iris structure. The performance of iris recognition across multiple wavelengths is next evaluated. Experiments indicate the potential of using multispectral information to enhance the performance of iris recognition systems.

关键词： Pigmentation Anatomy Muscles Connective tissue Reflectivity Focusing Iris recognition pattern analysis computer science USA Councils

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Dynamics Based Robust Motion Segmentation

Dynamics Based Robust Motion Segmentation

引用

conference on computer vision and pattern recognition (CVPR)

作者： R. Lublinerman M. Sznaier O. Camps Department of Computer Science and Engineering Pennsylvania State University University Park PA USA Department of Electrical Engineering Pennsylvania State University University Park PA USA

In this paper we consider the problem of segmenting multiple rigid motions using multi-frame point correspondence data. The main idea of the method is to group points according to the complexity of the model required to explain their relative motion. Intuitively, this formalizes the idea that points on the same rigid share more modes of motion (for instance a common translation or rotation) than points on different objects, leading to less complex models. By exploiting results from systems theory, the problem of estimating the complexity of the underlying model is reduced to simply computing the rank of a matrix constructed from the correspondence data. This leads to a simple segmentation algorithm, computationally no more expensive than a sequence of SVDs. Since the proposed method exploits both spatial and temporal constraints, is less sensitive to the effect of noise or outliers than approaches that rely solely on factorizations of the measurements matrix. In addition, the method can also naturally handle "degenerate cases", e.g. cases where the objects partially share motion modes. These results are illustrated using several examples involving both degenerate and non-degenerate cases.

关键词： Robustness Motion segmentation computer vision Propellers Airplanes computer science Data engineering Noise measurement Geometrical optics Optical sensors

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A New Deformable Model for Boundary Tracking in Cardiac MRI and Its Application to the Detection of Intra-Ventricular Dyssynchrony

A New Deformable Model for Boundary Tracking in Cardiac MRI ...

引用

conference on computer vision and pattern recognition (CVPR)

作者： P.F.U. Gotardo K.L. Boyer J. Saltz S.V. Raman Department of Electrical and Computer Engineering Ohio State Uinversity Columbus OH USA Department of Biomedical Informatics Ohio State Uinversity Columbus OH USA

We present a new deformable model technique following a snake-like approach and using a complex Fourier shape descriptors parameterization to efficiently formulate the forces that constrain contour deformation. The method was successfully applied to track the left ventricle’s (LV) endocardial and epicardial boundaries in sequences of shortaxis magnetic resonance images depicting complete cardiac cycles. The extracted shapes show the method’s robustness to weak contrast, noisy edge maps and to papillary muscle anatomy. Our second contribution is a statistical pattern recognition approach for the detection of asynchronous activation of the LV walls. We applied our deformable model method to provide spatio-temporal characterizations of complete cardiac cycles and then designed a linear classifier using the popular combination of Principal Component Analysis and Linear Discriminant Analysis. From a database comprising 33 patients, our approach provided a correct classification performance of 90.9% showing its potential in providing improved dyssynchrony characterization as an adjunct to current criteria for selecting patients for therapy, which provided a classification accuracy of just 62.5% on the same database.

关键词： Deformable models Magnetic resonance imaging Shape Databases Magnetic resonance Robustness Magnetic noise Noise shaping Image edge detection Muscles

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Good Continuation in Layers: Shading flows, color flows, surfaces and shadows

Good Continuation in Layers: Shading flows, color flows, sur...

引用

ieee computer society conference on computer vision and pattern recognition Workshops (CVPRW)

作者： O. Ben-Shahar A. Glaser S.W. Zucker Computer Science Ben-Gurion University of the Negev Israel Applied Mathematics Yale University New Heaven CT USA Computer Science Yale University New Heaven CT USA

We extend the concept of good continuation in a uniform fashion from boundaries to shading, hue, and texture. Each has the property that local measurements yield an orientation, which we explicitly establish for hue using geometric harmonic techniques. Good continuation arises in a geometric sense, because these orientations all vary smoothly in an appropriate sense. Thus they correspond to flows. Taken together they define a layered set of flows, in the sense the "horizontal" computations within each flow provide global consistency while "vertical" computations across flows enable the identification of shading and shadowing and different types of edges. Evidence is reviewed that primate visual systems enjoy such an organization.

关键词： computer science Computed tomography Shadow mapping Visual system computer vision Surface texture Mathematics Color Image segmentation Light sources

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