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A tracking-by-detection framework is proposed that combines nearest-neighbor classification of bags of features, efficient subwindow search, and a novel feature selection and pruning method to achieve stability and plasticity in tracking targets of changing appearance. Experiments show that near-frame-rate performance is achieved (sans feature detection),(More)
We study the 3D reconstruction of plant roots from multiple 2D images. To meet the challenge caused by the delicate nature of thin branches, we make three innovations to cope with the sensitivity to image quality and calibration. First, we model the background as a harmonic function to improve the segmentation of the root in each 2D image. Second, we(More)
We propose new ideas and efficient algorithms towards bridging the gap between bag-of-features and constellation descriptors for image matching. Specifically, we show how to compute connections between local image features in the form of a critical net whose construction is repeatable across changes of viewing conditions or scene configuration. Arcs of the(More)
Offline tracking of visual objects is particularly helpful in the presence of significant occlusions, when a frame-by-frame, causal tracker is likely to lose sight of the target. In addition, the trajectories found by offline tracking are typically smoother and more stable because of the global optimization this approach entails. In contrast with previous(More)
Many computer vision systems approximate targets' shape with rectangular bounding boxes. This choice trades localization accuracy for efficient computation. We propose twisted window search, a strict generalization over rectangular window search, for the globally optimal localization of a target's shape. Despite its generality, we show that the new(More)
We present a nonparametric and efficient method for shape localization that improves on the traditional sub-window search in capturing the fine geometry of an object from a small number of feature points. Our method implies that the discrete set of features capture more appearance and shape information than is commonly exploited. We use the a-complex by(More)
We consider labeling an image with multiple tiers. Tiers, one on top of another, enforce a strict vertical order among objects (e.g. sky is above the ground). Two new ideas are explored: First, under a simplification of the general tiered labeling framework proposed by Felzenszwalb and Veksler [1], we design an efficient O(KN) algorithm for the approximate(More)
The analysis of complex human activity typically requires multiple sensors: cameras that take videos from different directions and in different areas, microphones, proximity sensors, range finders, and more. Scenarios where it is not possible to associate reliable clocks to each of the sensors pose a synchronization problem between heterogeneous data(More)
Topological persistence measures the resilience of extrema of a function to perturbations, and has received increasing attention in computer graphics, visualization and computer vision. While the notion of topological persistence for piece-wise linear functions defined on a simplicial complex has been well studied, the time complexity of all the known(More)
" Architecture-driven synthesis techniques for mapping digital signal processing algorithms into silicon, " FSMs have a clear and unambiguous notion of a quantum of computation (one state transition), the problem reduces to determining what a quantum of computation is in the semantic model used to manage the concurrency and communication. This model could(More)