Recent work by Mullane, Vo, and Adams has re-examined the probabilistic foundations of feature-based Simultaneous Localization and Mapping (SLAM), casting the problem in terms of filtering with random finite sets. Alg...
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Recent work by Mullane, Vo, and Adams has re-examined the probabilistic foundations of feature-based Simultaneous Localization and Mapping (SLAM), casting the problem in terms of filtering with random finite sets. Algorithms were developed based on Probability Hypothesis Density (PHD) filtering techniques that provided superior performance to leading feature-based SLAM algorithms in challenging measurement scenarios with high false alarm rates, high missed detection rates, and high levels of measurement noise. We investigate this approach further by considering a hierarchical point process, or single-cluster multi-object, model, where we consider the state to consist of a map of landmarks conditioned on a vehicle state. Using Finite Set Statistics, we are able to find tractable formulae to approximate the joint vehicle-landmark state based on a single Poisson multi-object assumption on the predicted density. We describe the single-cluster PHD filter and the practical implementation developed based on a particle-system representation of the vehicle state and a Gaussian mixture approximation of the map for each particle. Synthetic simulation results are presented to compare the novel algorithm against the previous PHD filter SLAM algorithm. Results presented indicate a superior performance in vehicle and map landmark localization, and comparable performance in landmark cardinality estimation.
In this paper, we present an inexpensive system for diverless video capture and fast image stitching of image frames for rapid reef assessment of shallow coral reefs. Our system has two main components: 1) Teardrop, a...
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In this paper, we present an inexpensive system for diverless video capture and fast image stitching of image frames for rapid reef assessment of shallow coral reefs. Our system has two main components: 1) Teardrop, a...
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In this paper, we present an inexpensive system for diverless video capture and fast image stitching of image frames for rapid reef assessment of shallow coral reefs. Our system has two main components: 1) Teardrop, a boat-towable, winged hull apparatus designed to house a commercial digital camera, and 2) a mosaicking algorithm to stitch the coral reef video into mosaics for further appreciation and analysis. The captured reef video is then separated into image frames which are to be stitched sequentially using Fast image Labeling. The overlap between image frames is estimated using Single-Step DFT, an efficient sub-pixel estimation algorithm. The estimated overlap is used to compute for the area to be added to the mosaic space. The overlapping section between succeeding image-pairs are stitched along a seam determined by a minimal-cost path using dynamic programming. The visibility of the seam boundaries is further minimized by utilizing blending on multi-resolution splines. Experimental results on automated reef mosaics creation from actual coral reef video taken using Teardrop shows the performance of the system described. The main contribution of this work is the demonstration of a rapid reef visualization system using a diverless system and commercially available, non-research-grade imaging equipment.
In this paper examination of the template modeling process using the Active Appearance Modeling (AAM) approach for automatic detection of lung nodules is investigated. A template matching approach is formulated to com...
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In this paper examination of the template modeling process using the Active Appearance Modeling (AAM) approach for automatic detection of lung nodules is investigated. A template matching approach is formulated to compute a similarity score between the AAM templates and the input lung CT slice, where the goal is to maximize the similarity measure at different image pixels to increase nodule detection. The template matching approach is implemented using nine similarity measures. Performance validation for the robustness of the generated models is tested on three clinical databases.
In this, paper a new approach for lung nodules detection from LDCT scans is proposed. Intensity models of the nodules are generated using an active appearance model formulation. Template matching is used to compute a ...
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ISBN:
(纸本)9781457718571
In this, paper a new approach for lung nodules detection from LDCT scans is proposed. Intensity models of the nodules are generated using an active appearance model formulation. Template matching is used to compute a similarity score between the AAM template and the input image. The goal is to maximize the similarity measure at different image pixels to increase nodule detection. Conventional template matching does not account for rotation variations. Our proposed template matching approach is formulated as an energy optimization problem that computes a transformation that includes rotation(s) parameters as well as the AAM weighting coefficients. The approach is flexible to different scans and different nodule locations because of the ability to handle the variations in the rotation between the template and the input images. The approach can employ different similarity measures. Experimental results will be shown using three similarity measures from the literature: NCC, ZNCC and ZSSD; which illustrate the efficiency of the proposed approach. ROC curves for various nodule types are constructed on a clinical study with known ground truth, showing significant enhancements over conventional parametric nodule models and traditional template matching criterion.
We present a rapid shallow coastal reef mapping system using a previously developed inexpensive diver less video capture system coupled with a fast-image mosaicking technique, using an affordable GPS logging device. T...
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We present a rapid shallow coastal reef mapping system using a previously developed inexpensive diver less video capture system coupled with a fast-image mosaicking technique, using an affordable GPS logging device. The system replaces the traditional manta tow system of assessing and monitoring large areas of coastal coral reefs and at the same time provides historical visual record for future references. The system utilizes Teardrop, a hollow, teardrop-shaped that houses a commercial underwater point-and-shoot camera. The camera is set to video mode and captures video of the reef while the Teardrop is being towed by a wooden fishing boat. The resulting video is parsed into frames and mosaicked by using fast image labeling. The approximate location of the mosaicked images is recorded by using an inexpensive GPS logger. The coordinates are embedded on the mosaicked images and overlaid on mapping software such as Google Earth for visual record and spatial information integration. The same points are used to compute for the total distance covered by the capturing process. The whole process from coral reef video capture to mosaicking the images and finally embedding the mosaics in mapping software can be done in as short as 1 day, providing coastal managers and local government units with a tool to rapidly visualize and monitor shallow coral reefs.
This paper proposes a framework for face recognition at a distance based on texture, Sparse-Stereo, and Dense-stereo reconstruction. We develop a 3D acquisition system that consists of two CCD stereo cameras mounted o...
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ISBN:
(纸本)9781612847719
This paper proposes a framework for face recognition at a distance based on texture, Sparse-Stereo, and Dense-stereo reconstruction. We develop a 3D acquisition system that consists of two CCD stereo cameras mounted on pan-tilt units with adjustable baseline. In this paper we introduce our stereo-based indoor/outdoor environment and different ranges human faces database. Also, we propose a front-to-end system of 3D face reconstruction and recognition. We first detect the facial region and extract its landmark points, which are used to initialize the face alignment algorithm. The fitted mesh vertices, generated from the face alignment process, provide point correspondences between the left and right images of a stereo pair; stereo-based reconstruction is then used to infer the 3D information of the mesh vertices. Also the dense 3D is reconstructed for the cropped stereo pair based on graph cut approach. We perform experiments regarding the use of different features extracted from these vertices for face recognition. The cumulative rank curves (CMC), which are generated using the proposed framework, confirm the feasibility of the proposed work for long distance recognition of human faces.
In this paper we propose a robust method for geometric co registration, and an accurate change detection technique based on statistical method for multi-temporal high-resolution satellite imagery. Lhe proposed algorit...
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ISBN:
(纸本)9781612847719
In this paper we propose a robust method for geometric co registration, and an accurate change detection technique based on statistical method for multi-temporal high-resolution satellite imagery. Lhe proposed algorithm is as the following: scale-invariant feature transform (SIFT) is used to extract a set of correspondence points in a pair, or multiple pairs, of images that are taken at different times and under different circumstances, then Random Sample Consensus (RANSAC) is used to remove the outlier set. the resulting inliers matched points is an accurate correspondences which used to register the given images, changes in registered images are identified using statistical analysis of image differences. Finally, Markov-Gibbs Random Field (MGRF) is used to model the spatial-contextual information contained in the resulting change mask. Experiments with generated synthetic multiband images, and LANDSAT5 images, approved the accuracy the proposed algorithm.
Measuring the similarity between articulated shapes is a fundamental yet challenging problem. This paper proposes a novel shape descriptor based on Width Distributions (WD), which is robust to articulations. We show t...
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Despite their high popularity, common high dynamic range (HDR) methods are still limited in their practical applicability: They assume that the input images are perfectly aligned, which is often violated in practise. ...
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