We present a novel technique for image driven shot retrieval in video data. Specifically, given a query image, our method can efficiently pick the video segment containing that image. Video is first divided into shots...
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ISBN:
(纸本)9780769549835
We present a novel technique for image driven shot retrieval in video data. Specifically, given a query image, our method can efficiently pick the video segment containing that image. Video is first divided into shots. Each shot is described using an embedded hidden Markov model (EHMM). the EHMM is trained on GIST-like descriptors of frames in that shot. the trained EHMM computes the likelihood that a query image belongs to the shot. A Support Vector Machine classifier is trained for each EHMM. the classifier provides a yes/no decision given the likelihood value produced by its EHMM. Given a collection of shot models from one or more videos, the proposed technique can efficiently decide whether or not an image belongs to a video by identifying the shot most likely to contain that image. the proposed technique is evaluated on a realistic dataset.
We present a new scheme for partitioning geo-tagged reference image database in an effort to speed up (query) image localization while maintaining acceptable localization accuracy. Our method learns a topic model over...
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ISBN:
(纸本)9780769549835
We present a new scheme for partitioning geo-tagged reference image database in an effort to speed up (query) image localization while maintaining acceptable localization accuracy. Our method learns a topic model over the reference database, which in turn is used to divide the reference database into scene groups. Each scene group consists of "visually similar" images as determined by the topic model. Next raw Scale-Invariant Feature Transform (SIFT) features are collected from every image in a scene group a Fast Library for Approximate Nearest Neightbours (FLANN) index is constructed. Given a query image, first its scene group is determined using the topic model and then its SIFT features are matched against the corresponding FLANN index. the query image is localized using the location information from the visually similar images in the reference database. We evaluate our approach on Google Map Street View dataset and demonstrate that our method outperforms a competing technique.
We present a novel approach to reconstructing cities and buildings from LIDAR data using level set methods. Traditional approaches to building extraction from LIDAR data use image segmentation algorithms to determine ...
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ISBN:
(纸本)9780769549835
We present a novel approach to reconstructing cities and buildings from LIDAR data using level set methods. Traditional approaches to building extraction from LIDAR data use image segmentation algorithms to determine the outlines of rooftops, estimation of height/depth maps, polygonal mesh generation and extrusion to generate 3D models resulting in buildings with high quality rooftops but flat sides with little or no detail shown on vertical surfaces (e. g. overhangs and windows on walls). Texturing these flat side polygons with aerial and geo-registered ground imagery create acceptable photo-realistic models although the resulting buildings are generally not geometrically accurate causing stretching and waviness in texture-mapping. Our approach uses the LIDAR data directly as constraints in a variational framework and can estimate the geometry more accurately and demonstrate its effectiveness with simulated data.
the paper focuses on robust 3D structure from motion of nonrigid objects from uncalibrated image sequences. A new affine factorization algorithm is first proposed to avoid the difficulty in image alignment for imperfe...
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ISBN:
(纸本)9780769549835
the paper focuses on robust 3D structure from motion of nonrigid objects from uncalibrated image sequences. A new affine factorization algorithm is first proposed to avoid the difficulty in image alignment for imperfect data, followed by a robust factorization scheme to handle outlying and missing data. the novelty and main contributions of the paper are as follows: (i) as a new addition to previous nonrigid structure from motion, the proposed factorization algorithm can perfectly handle imperfect tracking data;(ii) it is demonstrated that the image reprojection residuals are in general proportional to the error magnitude of the tracked features. thus, the outliers can be detected directly from the residuals, which are then used to estimate the uncertainties of the image measurement;and (iii) the robust factorization scheme is proved empirically to be more efficient and more accurate than other robust algorithms. the proposed approach is validated and evaluated by extensive experiments on synthetic data and real image sequences.
In this paper, a shape recognition method is proposed for a few common geometrical shapes including straight line, circle, ellipse, triangle, quadrilateral, pentagon and hexagon. In the present work, two indices namel...
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ISBN:
(纸本)9781479915880
In this paper, a shape recognition method is proposed for a few common geometrical shapes including straight line, circle, ellipse, triangle, quadrilateral, pentagon and hexagon. In the present work, two indices namely Unique Shape Signature (USS) and Condensibility (C) are employed for shape recognition of an object. Using the USS index, all the above mentioned non-circular shapes are neatly recognized, whereas, the C index recognized the circular objects. An added advantage of the proposed method is that it can further differentiate triangles, quadrilaterals and both symmetric and non-symmetric shapes of pentagon and hexagon using distance variance (Var(d(si))) parameter calculated from USS. Applying the proposed method on above mentioned shapes, an overall recognition rate of 98.80% is achieved on several simulated and real objects of different shapes. Proposed method has also been compared with two existing methods, presents better result. Performance of the proposed method is illustrated by applying it on underwater images and it is observed to perform satisfactory on all the images under test.
Dynamic textures are sequences of images of moving scenes in time that are common in natural scenes and play an important role in video content analysis. this paper presents a new dynamic Bayesian framework for segmen...
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ISBN:
(纸本)9780769549835
Dynamic textures are sequences of images of moving scenes in time that are common in natural scenes and play an important role in video content analysis. this paper presents a new dynamic Bayesian framework for segmentation of dynamic textures. First, we formulate the problem in the Bayesian framework using mixture model theory. the major advantage of our approach is that it provides a natural way to cluster data based on the components of the mixture that generated it. Second, in order to model the distribution of observed data, only grayscale information is taken into consideration of the existing mixture models. In order to overcome this problem, a new distribution is presented in this paper. the advantage of the proposed distribution is that it has the flexibility to fit different kinds of observed data and is more reliable for changes of noise and contrast levels. Finally, expectation maximization (EM) algorithm is adopted to maximize the lower bound on the data log-likelihood and to optimize the parameters. the proposed model is successfully compared to the state of the arts dynamic texture segmentation approaches. Numerous experiments are presented where our model is tested on various simulated and natural real-world dynamic textures.
Tracking storms in radar images can be conceived of as a problem of tracking deformable objects. Our current relaxation labelling-based tracking algorithm that represents these deformable objects as "fuzzy" ...
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ISBN:
(纸本)9780769549835
Tracking storms in radar images can be conceived of as a problem of tracking deformable objects. Our current relaxation labelling-based tracking algorithm that represents these deformable objects as "fuzzy" points can track objects that undergo shape deformations. One other type of deformation is the splitting of an object into multiple objects or the merging of multiple objects into one object from one image to the next. With our current algorithm, tracks are interrupted when such events happen in image sequences. We remove this deficiency of the current algorithm by adding the concept of a Pseudo Storm to its representational repertoire. With only minor modifications to the current algorithm, the new algorithm can track deformable objects that undergo both merging and splitting events. the new pseudo storm tracking algorithm outperforms our previous storm tracking algorithm for Great Lakes Doppler precipitation datasets.
this Paper will introduce methods used to resolve self-location problem of humanoid robots. there are two method that will be mentioned in this paper. A traditional method which uses marks and flags on the soccer fiel...
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the system uses three-dimensional measurement of binocular visiontheory, through optical, mechanical, computer and other aspects of the technology to measure the target without contact, and up to a certain precision....
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ISBN:
(纸本)9783037858813
the system uses three-dimensional measurement of binocular visiontheory, through optical, mechanical, computer and other aspects of the technology to measure the target without contact, and up to a certain precision. In the high-voltage area, high-altitude target,and the target which is not easy to touch, there is a unique measure advantage. Binocular stereo vision is based on the principle of parallax and using imaging devices from different locations to obtain two images of the measured object and obtain three dimensional geometric of target by positional deviation between corresponding points in computer image. Binocular stereo currently used in four areas: robot navigation, micro operating system parameter detection, three-dimensional measurements and virtual reality. In addition, the system not only to measure the length of the distant object, the system can also be used to measure the width, surface area, height and tilt angle. As the tip of an optical imaging technology this system has a broad application prospects in the future.
We propose a point cloud data acquisition system that employs slit ray projection. In this system, a slit laser projector and a high-resolution CCD camera are connected to a Microsoft Kinect Sensor. the system is suff...
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ISBN:
(纸本)9780819495662
We propose a point cloud data acquisition system that employs slit ray projection. In this system, a slit laser projector and a high-resolution CCD camera are connected to a Microsoft Kinect Sensor. the system is sufficiently compact that it can be hand held. In measurements of pipes, the user directs the laser slit ray at the measurement target. Kinect then detects point cloud data while the CCD camera simultaneously detects the laser streak generated on the target surface. the user manually scans the system by directing the laser slit ray along the measurement pipe. the point cloud data obtained by Kinect is used to determine the movement of the system by adjusting overlapping data in consecutive frames using the ICP (Iterative Closest Point) algorithm. this permits the system to be freely scanned. the pipe cross section is estimated from data obtained by the slit-ray projection method. the three-dimensional shape of the pipe is constructed on a computer from the obtained cross sections.
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