We propose an algorithm for the on-line automatic registration of multiple 3D surfaces acquired in a sequence by a new hand-held laser scanner. The laser emitter is coupled with an optical lens that spreads the light ...
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We propose an algorithm for the on-line automatic registration of multiple 3D surfaces acquired in a sequence by a new hand-held laser scanner. The laser emitter is coupled with an optical lens that spreads the light forming 19 parallel slits that are projected to the scene and acquired with subpixel accuracy by a camera. Splines are used to interpolate the acquired profiles to increase the sample of points and Delaunay triangulation is used to obtain the normal vectors at every point. A point-to-plane pair-wise registration method is proposed to align the surfaces in pairs while they are acquired, conforming paths and eventually cycles that are minimized once detected. The algorithm is specially designed for on-line applications and can be classified as a closing-the-loop technique, where there are not that many competing methods, though it has been compared to the literature. Experiments providing qualitative and quantitative evaluation are shown by means of synthetic and real data and we demonstrated the reliability of our technique. (C) 2007 Elsevier Ltd. All rights reserved.
A robust method for tracking faces of multiple people moving in a scene using Kalman filter is proposed in this paper. To distinguish faces of people during partial occlusion the proposed method uses the non-parametri...
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We describe a method for registering and super-resolving moving vehicles from aerial surveillance video. The challenge of vehicle super-resolution lies in the fact that vehicles may be very small and thus frame-to-fra...
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A closed form solution to the problem of segmenting multiple 3D motion models was proposed from straight-line optical flow. It introduced the multibody line optical flow constraint (MLOFC), a polynomial equation relat...
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A closed form solution to the problem of segmenting multiple 3D motion models was proposed from straight-line optical flow. It introduced the multibody line optical flow constraint (MLOFC), a polynomial equation relating motion models and line parameters. The motion models can be obtained analytically as the derivative of the MLOFC at the corresponding line measurement, without knowing the motion model associated with that line. Experiments on real and synthetic sequences were also presented.
Statistical learning based face detection systems search multiple scale sub-frames of an image or frame of a video stream with a trained classifier to detect face objects. If the frame is large there will be a large n...
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Image moments are used in image analysis for object modelling and matching. The moment computation of a two-dimensional (213) image involves a significant amount of multiplication and addition in a direct method. In t...
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Image moments are used in image analysis for object modelling and matching. The moment computation of a two-dimensional (213) image involves a significant amount of multiplication and addition in a direct method. In this paper, we use the suffix sum functions to compute the gray-level image moments instead of using a direct method. This new method can reduce drastically the number of multiplications required. We first derive the mathematical relationships between moment computations and suffix sums. Based on the derived mathematical relationships, four new parallel algorithms for computing image moments are derived on various computational models. By integrating the advantages of both optical transmission and electronic computation, the 2D image moments can be computed in constant time on a 2D array with reconfigurable optical buses. The performance comparison shows that the proposed method is fast and efficient. In addition, three scalable and cost optimal algorithms are derived on the AROB, the hypercube computer and the EREW PRAM model. (c) 2007 Elsevier B.V. All rights reserved.
This paper presents a homotopy-based algorithm for a simultaneous recovery of defocus blur and the affine parameters of apparent shifts between planar patches of two pictures. These parameters are recovered from two i...
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This paper presents a homotopy-based algorithm for a simultaneous recovery of defocus blur and the affine parameters of apparent shifts between planar patches of two pictures. These parameters are recovered from two images of the same scene acquired by a camera evolving in time and/or space and for which the intrinsic parameters are known. Using limited Taylor's expansion one of the images (and its partial derivatives) is expressed as a function of the partial derivatives of the two images, the blur difference, the affine parameters and a continuous parameter derived from homotopy methods. All of these unknowns can thus be directly computed by resolving a system of equations at a single scale. The proposed algorithm is tested using synthetic and real images. The results confirm that dense and accurate estimation of the previously mentioned parameters can be obtained. (c) 2007 Elsevier Ltd. All rights reserved.
Video smoke detection has many advantages over traditional methods, such as fast response, non-contact, and so on. But most of video smoke detection systems usually have high false alarms. In order to improve the perf...
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Video smoke detection has many advantages over traditional methods, such as fast response, non-contact, and so on. But most of video smoke detection systems usually have high false alarms. In order to improve the performance of video smoke detection, we propose an accumulative motion model based on the integral image by fast estimating the motion orientation of smoke. But the estimation is not very precise due to block sum. Not very accurate estimation will affect the subsequent decision. To reduce this influence, the accumulation of the orientation over time is performed to compensate results for the inaccuracy of orientation. The model is able to mostly eliminate the disturbance of artificial lights and non-smoke moving objects by using the accumulation of motion. The model together with chrominance detection can correctly detect the existence of smoke. Experimental results show that our algorithm has good robustness for smoke detection. (C) 2008 Elsevier B.V. All rights reserved.
Automatic separation of text and symbols from graphics in document image is one of the fundamental aims in graphics recognition. In maps, separation of text and symbols from graphics involves many challenges because t...
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