In this paper we present an efficient hierarchical approach to structure from motion for long image sequences. There are two key elements to our approach: accurate 3D reconstruction for each segment and efficient bund...
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In this paper we present an efficient hierarchical approach to structure from motion for long image sequences. There are two key elements to our approach: accurate 3D reconstruction for each segment and efficient bundle adjustment for the whole sequence. The image sequence is first divided into a number of segments so that feature points can be reliably tracked across each segment. Each segment has a long baseline to ensure accurate 3D reconstruction. To efficiently bundle adjust 3D structures from all segments, we reduce the number of frames in each segment by introducing `virtual key frames'. The virtual frames encode the 3D structure of each segment along with its uncertainty but they form a small subset of the original frames. Our method achieves significant speedup over conventional bundle adjustment methods.
The scale-space representations and wavelet transform theory have provided us with good singularity detection frameworks. Thanks to such methods, image understanding processes have become more and more powerful. Some ...
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ISBN:
(纸本)0818658258
The scale-space representations and wavelet transform theory have provided us with good singularity detection frameworks. Thanks to such methods, image understanding processes have become more and more powerful. Some computervision tasks also require a knowledge on the nature of detected singularities. We propose, in this paper, to take into account these requirements, and we present a singularity detection method based on fractional calculus arguments.
The appearance of a particular object depends on both the viewpoint from which it is observed and the light sources by which it is illuminated. If the appearance of two objects is never identical for any pose or light...
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ISBN:
(纸本)0818672587
The appearance of a particular object depends on both the viewpoint from which it is observed and the light sources by which it is illuminated. If the appearance of two objects is never identical for any pose or lighting conditions, then - in theory - the objects can always be distinguished or recognized. The question arises: What is the set of images of an object under all lighting conditions and pose? In this paper, we consider only the set of images of an object under variable illumination (including multiple, extended light sources and attached shadows). We prove that the set of n-pixel images of a convex object with a Lambertian reflectance function, illuminated by an arbitrary number of point light sources at infinity, forms a convex polyhedral cone in Rn and that the dimension of this illumination cone equals the number of distinct surface normals. Furthermore, we show that the cone for a particular object can be constructed from three properly chosen images. Finally, we prove that the set of n-pixel images of an object of any shape and with an arbitrary reflectance function, seen under all possible illumination conditions, still forms a convex cone in Rn. These results immediately suggest certain approaches to object recognition. Throughout this paper, we offer results demonstrating the empirical validity of the illumination cone representation.
A new framework and method, based on image motion trajectories in spatiotemporal space(x-y-t space), are proposed to estimate image velocity from an image sequence. We focus on the surfaces of the trajectories in the ...
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ISBN:
(纸本)0818678224;0780342364
A new framework and method, based on image motion trajectories in spatiotemporal space(x-y-t space), are proposed to estimate image velocity from an image sequence. We focus on the surfaces of the trajectories in the x-y-t space formed by the edges and contours of moving objects and obtain image velocity from the orientation of the intersection line formed by tangent planes on the trajectories. The proposed method includes two Hough transforms to detect the most dominant orientation in all possible intersection lilies and reliably produces the dominant translational image velocity semi-locally. Also, the confidence measure of estimates is defined to decide the optimal size of patch that suppresses the aperture problem. Experimental results from several synthetic and real image sequences are presented to verify the effectiveness of the method and to confirm its robustness against noise and occlusion.
Recently, rue have proposed a new approach to estimation of the coefficients of eigenimages, which is robust against occlusion, varying background: and other types of non-Gaussian noise [4, 5]. In this paper we show t...
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ISBN:
(纸本)0818684976
Recently, rue have proposed a new approach to estimation of the coefficients of eigenimages, which is robust against occlusion, varying background: and other types of non-Gaussian noise [4, 5]. In this paper we show that our method for estimating the coefficients can be applied to convolved and subsampled images yielding the same value of the coefficients. This enables an efficient multiresolution approach, where the values of the coefficients can directly be propagated through the scales. This property is used to extend oar robust method to the problem of scaled images. We performed extensive experimental evaluations to confirm, our theoretical results.
Markov Random Fields (MRF's) can be used for a wide variety of vision problems, fn this paper we focus on MRF's with two-valued clique potentials, which form a generalized Potts model, We show that the maximum...
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ISBN:
(纸本)0818684976
Markov Random Fields (MRF's) can be used for a wide variety of vision problems, fn this paper we focus on MRF's with two-valued clique potentials, which form a generalized Potts model, We show that the maximum a posteriori estimate of such an MRF can be obtained by solving a multiway minimum cut problem on a graph. We develop efficient algorithms Sar computing good approximations to the minimum multiway cut. The visual correspondence problem can be formulated as an MRF in our framework this yields quite promising results on real data with ground truth. We also apply our techniques to MRF's with linear clique potentials.
We describe a vision system that monitors activity in a Site over extended periods of time. The system uses a distributed set of sensors to cover the site, and an adaptive trader detects multiple moving objects in the...
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ISBN:
(纸本)0818684976
We describe a vision system that monitors activity in a Site over extended periods of time. The system uses a distributed set of sensors to cover the site, and an adaptive trader detects multiple moving objects in the sensors. Our hypothesis is that motion tracking is sufficient to support a range of computations about site activities. I We demonstrate using the tracked motion data: to calibrate the distributed sensors, to con Struct rough Site models, to classify detected objects, to learn common patterns of activity for different object classes, and to detect unusual activities.
This work presents AFRIFASHION1600, an openly accessible contemporary African fashion image dataset containing 1600 samples labelled into 8 classes representing some African fashion styles. Each sample is coloured and...
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ISBN:
(纸本)9781665448994
This work presents AFRIFASHION1600, an openly accessible contemporary African fashion image dataset containing 1600 samples labelled into 8 classes representing some African fashion styles. Each sample is coloured and has an image size of 128 x 128. This is a niche dataset that aims to improve visibility, inclusion, and familiarity of African fashion in computervision ***1600 dataset is available here.
Detecting suspicious events from video surveillance cameras has been an important task recently. Many trajectory based descriptors were developed, such as to detect people running or moving in opposite direction. Howe...
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ISBN:
(纸本)9781424439942
Detecting suspicious events from video surveillance cameras has been an important task recently. Many trajectory based descriptors were developed, such as to detect people running or moving in opposite direction. However, these trajectory based descriptors are not working well in the crowd environments like airports, rail stations, because those descriptors assume perfect motion/object segmentation. In this paper, we present an event detection method using dynamic texture descriptor. The dynamic texture descriptor is an extension of the local binary patterns. The image sequences are divided into regions. A flow is formed based on the similarity of the dynamic texture descriptors on the regions. We used real dataset for experiments. The results are promising.
Given a machine learning model, adversarial perturbations transform images such that the model's output is classified as an attacker chosen class. Most research in this area has focused on adversarial perturbation...
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ISBN:
(数字)9781538661000
ISBN:
(纸本)9781538661000
Given a machine learning model, adversarial perturbations transform images such that the model's output is classified as an attacker chosen class. Most research in this area has focused on adversarial perturbations that are imperceptible to the human eye. However, recent work has considered attacks that are perceptible but localized to a small region of the image. Under this threat model, we discuss both defenses that remove such adversarial perturbations, and attacks that can bypass these defenses.
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