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Detection and tracking of point features (1991)

by C Tomasi, T Kanade
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Evaluation of Interest Point Detectors

by Cordelia Schmid, Roger Mohr, Christian Bauckhage , 2000
"... Many different low-level feature detectors exist and it is widely agreed that the evaluation of detectors is important. In this paper we introduce two evaluation criteria for interest points: repeatability rate and information content. Repeatability rate evaluates the geometric stability under diff ..."
Abstract - Cited by 414 (8 self) - Add to MetaCart
Many different low-level feature detectors exist and it is widely agreed that the evaluation of detectors is important. In this paper we introduce two evaluation criteria for interest points: repeatability rate and information content. Repeatability rate evaluates the geometric stability under different transformations. Information content measures the distinctiveness of features. Different interest point detectors are compared using these two criteria. We determine which detector gives the best results and show that it satisfies the criteria well.
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...is located between these two points at the zero crossing of DET . Nagel [32] shows that the Dreschler-Nagel's approach and Kitchen-Rosenfeld's approach are identical. Several interest point detectors =-=[17, 18, 19, 48]-=- are based on a matrix related to the autocorrelation function. This matrix A averages derivatives of the signal in a window W around a point (x; y) : A(x; y) = 2 6 6 6 6 4 P (x k ;y k )2W (I x (x k ;...

An Image-Based Approach to Three-Dimensional Computer Graphics

by Leonard McMillan, Jr. , 1997
"... The conventional approach to three-dimensional computer graphics produces images from geometric scene descriptions by simulating the interaction of light with matter. My research explores an alternative approach that replaces the geometric scene description with perspective images and replaces the s ..."
Abstract - Cited by 207 (5 self) - Add to MetaCart
The conventional approach to three-dimensional computer graphics produces images from geometric scene descriptions by simulating the interaction of light with matter. My research explores an alternative approach that replaces the geometric scene description with perspective images and replaces the simulation process with data interpolation. I derive an image-warping equation that maps the visible points in a reference image to their correct positions in any desired view. This mapping from reference image to desired image is determined by the center-of-projection and pinhole-camera model of the two images and by a generalized disparity value associated with each point in the reference image. This generalized disparity value, which represents the structure of the scene, can be determined from point correspondences between multiple reference images. The image-warping equation alone is insufficient to synthesize desired images because multiple reference-image points may map to a single point. I derive a new visibility algorithm that determines a drawing order for the image warp. This algorithm results in correct visibility for the desired image independent of the reference image’s contents. The utility of the image-based approach can be enhanced with a more general pinholecamera

Monocular model-based 3d tracking of rigid objects: A survey

by Vincent Lepetit, Pascal Fua - In Foundations and Trends in Computer Graphics and Vision , 2005
"... Many applications require tracking of complex 3D objects. These include visual servoing of robotic arms on specific target objects, Aug-mented Reality systems that require real-time registration of the object to be augmented, and head tracking systems that sophisticated inter-faces can use. Computer ..."
Abstract - Cited by 142 (4 self) - Add to MetaCart
Many applications require tracking of complex 3D objects. These include visual servoing of robotic arms on specific target objects, Aug-mented Reality systems that require real-time registration of the object to be augmented, and head tracking systems that sophisticated inter-faces can use. Computer Vision offers solutions that are cheap, practical and non-invasive. This survey reviews the different techniques and approaches that have been developed by industry and research. First, important math-ematical tools are introduced: Camera representation, robust estima-tion and uncertainty estimation. Then a comprehensive study is given of the numerous approaches developed by the Augmented Reality and Robotics communities, beginning with those that are based on point or planar fiducial marks and moving on to those that avoid the need to engineer the environment by relying on natural features such as edges, texture or interest. Recent advances that avoid manual initialization and failures due to fast motion are also presented. The survery con-cludes with the different possible choices that should be made when implementing a 3D tracking system and a discussion of the future of vision-based 3D tracking. Because it encompasses many computer vision techniques from low-level vision to 3D geometry and includes a comprehensive study of the massive literature on the subject, this survey should be the handbook of the student, the researcher, or the engineer who wants to implement a 3D tracking system. 1
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...discusses some efficient implementations using MMX instructions for both point extraction and matching. An alternative to matching points across images is to use the Kanade-Lucas-Tomasi (KLT) tracker =-=[83, 129, 116]-=-, which extracts points from an initial image and then tracks them in the following images by mostly relying on the optical flow. Both approaches have their strengths: KLT handles continuity better an...

Robust object tracking by hierarchical association of detection responses

by Chang Huang, Bo Wu, Ramakant Nevatia , 2008
"... Abstract. We present a detection-based three-level hierarchical association approach to robustly track multiple objects in crowded environments from a single camera. At the low level, reliable tracklets (i.e. short tracks for further analysis) are generated by linking detection responses based on co ..."
Abstract - Cited by 104 (10 self) - Add to MetaCart
Abstract. We present a detection-based three-level hierarchical association approach to robustly track multiple objects in crowded environments from a single camera. At the low level, reliable tracklets (i.e. short tracks for further analysis) are generated by linking detection responses based on conservative affinity constraints. At the middle level, these tracklets are further associated to form longer tracklets based on more complex affinity measures. The association is formulated as a MAP problem and solved by the Hungarian algorithm. At the high level, entries, exits and scene occluders are estimated using the already computed tracklets, which are used to refine the final trajectories. This approach is applied to the pedestrian class and evaluated on two challenging datasets. The experimental results show a great improvement in performance compared to previous methods. 1
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...re common. We propose a method that can robustly track multiple objects under such challenging conditions. Traditional feature-based tracking methods, such as those based on color [1], salient points =-=[2]-=- or motion blobs [3], do not have a discriminative model that distinguishes the object category of interest from others. Use of object detectors as discriminative models helps overcome this limitation...

Faster and better: a machine learning approach to corner detection

by Edward Rosten, Reid Porter, Tom Drummond , 2008
"... ..."
Abstract - Cited by 102 (0 self) - Add to MetaCart
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... the SSD is equal to the sum of the autocorrelation and some additional terms [46]. The earlier Förstner [47] algorithm is easily easily explained in terms of H. For a more recently proposed detector =-=[48]-=-, it has been shown shown [49] that under affine motion, it is October 14, 2008 DRAFT7 better to use the smallest eigenvalue of H as the corner strength function. A number of other suggestions [45], ...

Video copy detection: a comparative study

by Julien Law-to, Olivier Buisson, Li Chen, Martlesham Heath Ipswich, Valerie Gouet-brunet, Alexis Joly, Nozha Boujemaa, Ivan Laptev, Fred Stentiford, Martlesham Heath Ipswich - In CIVR , 2007
"... This paper presents a comparative study of methods for video copy detection. Different state-of-the-art techniques, using various kinds of descriptors and voting functions, are described: global video descriptors, based on spatial and temporal features; local descriptors based on spatial, temporal a ..."
Abstract - Cited by 86 (6 self) - Add to MetaCart
This paper presents a comparative study of methods for video copy detection. Different state-of-the-art techniques, using various kinds of descriptors and voting functions, are described: global video descriptors, based on spatial and temporal features; local descriptors based on spatial, temporal as well as spatio-temporal information. Robust voting functions is adapted to these techniques to enhance their performance and to compare them. Then, a dedicated framework for evaluating these systems is proposed. All the techniques are tested and compared within the same framework, by evaluating their robustness under single and mixed image transformations, as well as for different lengths of video segments. We discuss the performance of each approach according to the transformations and the applications considered. Local methods demonstrate their superior performance over the global ones, when detecting video copies subjected to various transformations. professionals. At the same time, controlling the copyright of the huge number of videos uploaded everyday is a critical challenge for the owner of the popular video web servers. Content Based Copy Detection (CBCD) presents an alternative to the watermarking approach to identify video sequences and to solve this challenge. The Robustness issue: Two videos which are copies
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...mputed around 4 spatial positions around the interest point (in the same frame). These points of interest are associated from frame to frame to build trajectories with an algorithm similar to the KLT =-=[22]-=-. For each trajectory, the signal description finally kept is the average of each component of the local description. By using the properties of the built trajectories, a label of behavior can be assi...

Unsupervised learning of human motion

by Yang Song, Luis Goncalves, Pietro Perona - IEEE Trans. PAMI , 2003
"... Abstract—An unsupervised learning algorithm that can obtain a probabilistic model of an object composed of a collection of parts (a moving human body in our examples) automatically from unlabeled training data is presented. The training data include both useful “foreground ” features as well as feat ..."
Abstract - Cited by 85 (1 self) - Add to MetaCart
Abstract—An unsupervised learning algorithm that can obtain a probabilistic model of an object composed of a collection of parts (a moving human body in our examples) automatically from unlabeled training data is presented. The training data include both useful “foreground ” features as well as features that arise from irrelevant background clutter—the correspondence between parts and detected features is unknown. The joint probability density function of the parts is represented by a mixture of decomposable triangulated graphs which allow for fast detection. To learn the model structure as well as model parameters, an EM-like algorithm is developed where the labeling of the data (part assignments) is treated as hidden variables. The unsupervised learning technique is not limited to decomposable triangulated graphs. The efficiency and effectiveness of our algorithm is demonstrated by applying it to generate models of human motion automatically from unlabeled image sequences, and testing the learned models on a variety of sequences. Index Terms—Unsupervised learning, human motion, decomposable triangulated graph, probabilistic models, greedy search, EM algorithm, mixture models. 1
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...m the specifics of the application, is that our method is unsupervised: it is based on unlabeled training data. The training sequence contains a number of bottom-up features (Tomasi and Kanade points =-=[30]-=- in our implementation) which are unlabeled, i.e., we do not know which features are associated to the body, which to background clutter, which features correspond to which features across image frame...

Tracking in Low Frame Rate Video: A Cascade Particle Filter with Discriminative Observers of Different Lifespans

by Yuan Li, Haizhou Ai
"... Tracking object in low frame rate video or with abrupt motion poses two main difficulties which conventional tracking methods can barely handle: 1) poor motion continuity and increased search space; 2) fast appearance variation of target and more background clutter due to increased search space. In ..."
Abstract - Cited by 81 (3 self) - Add to MetaCart
Tracking object in low frame rate video or with abrupt motion poses two main difficulties which conventional tracking methods can barely handle: 1) poor motion continuity and increased search space; 2) fast appearance variation of target and more background clutter due to increased search space. In this paper, we address the problem from a view which integrates conventional tracking and detection, and present a temporal probabilistic combination of discriminative observers of different lifespans. Each observer is learned from different ranges of samples, with different subsets of features, to achieve varying level of discriminative power at varying cost. An efficient fusion and temporal inference is then done by a cascade particle filter which consists of multiple stages of importance sampling. Experiments show significantly improved accuracy of the proposed approach in comparison with existing tracking methods, under the condition of low frame rate data and abrupt motion of both target and camera. 1.
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...dynamic model to guide the particle propagation within a limited sub-space of target state. Other methods based on iterative optimization such as mean shift [4] and KanadeLucas-Tomasi feature tracker =-=[17]-=- generally require the kernels or feature patches in consecutive frames to overlap with or be in a very close vicinity of each other. These, however, are presumptions too expensive under conditions of...

Towards Detection of Human Motion

by Yang Song, Xiaolin Feng, Pietro Perona - IN CVPR , 2000
"... Detecting humans in images is a useful application of computer vision. Loose and textured clothing, occlusion and scene clutter make it a difficult problem because bottom-up segmentation and grouping do not always work. We address the problem of detecting humans from their motion pattern in monocula ..."
Abstract - Cited by 75 (9 self) - Add to MetaCart
Detecting humans in images is a useful application of computer vision. Loose and textured clothing, occlusion and scene clutter make it a difficult problem because bottom-up segmentation and grouping do not always work. We address the problem of detecting humans from their motion pattern in monocular image sequences; extraneous motions and occlusion may be present. We assume that we may not rely on segmentation, nor grouping and that the vision front-end is limited to observing the motion of key points and textured patches in between pairs of frames. We do not assume that we are able to track features for more than two frames. Our method is based on learning an approximate probabilistic model of the joint position and velocity of different body features. Detection is performed by hypothesis testing on the maximum a posteriori estimate of the pose and motion of the body. Our experiments on a dozen of walking sequences indicate that our algorithm is accurate and efficient.

P.: “Image Analysis and Rule-Based Reasoning for a Traffic Monitoring System”, in

by Rita Cucchiara, Massimo Piccardi, Paola Mello - IEEE Transactions on Intelligent Transportation Systems , 2000
"... Abstract—The paper presents an approach for detecting vehicles in urban traffic scenes by means of rule-based reasoning on visual data. The strength of the approach is its formal sep-aration between the low-level image processing modules (used for extracting visual data under various illumination co ..."
Abstract - Cited by 73 (6 self) - Add to MetaCart
Abstract—The paper presents an approach for detecting vehicles in urban traffic scenes by means of rule-based reasoning on visual data. The strength of the approach is its formal sep-aration between the low-level image processing modules (used for extracting visual data under various illumination conditions) and the high-level module, which provides a general-purpose knowledge-based framework for tracking vehicles in the scene. The image-processing modules extract visual data from the scene by spatio-temporal analysis during daytime, and by morpho-logical analysis of headlights at night. The high-level module is designed as a forward chaining production rule system, working on symbolic data, i.e., vehicles and their attributes (area, pattern, direction, and others) and exploiting a set of heuristic rules tuned to urban traffic conditions. The synergy between the artificial intelligence techniques of the high-level and the low-level image analysis techniques provides the system with flexibility and robustness. Index Terms—Image analysis, knowledge-based systems, traffic monitoring, vehicle tracking. I.
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...orithms are known for detecting moving points, with different performance and time complexity. They belong to two main categories: optical-flow algorithms and frame-differencing algorithms [1], [20], =-=[25]-=-. Optical-flow algorithms are capable of computing motion magnitude and direction for each image point with high accuracy; at the same time, they require very high computational time and thus do not m...

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