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Together with the growing interest in the development of human and computer interface and biometric identification, human face recognition has become an active research area since early 90psilas. A number of current face recognition algorithms using face representations found by unsupervised statistical methods. Typically these methods find a set of basis images and represent faces as a linear combination...
Phase-based optical flow algorithms are characterized by high precision and robustness, but also by high computational requirements. Using the CUDA platform, we have implemented a phase-based algorithm that maps exceptionally well on the GPUpsilas architecture. This optical flow algorithm revolves around a reliability measure that evaluates the consistency of phase information over time. By exploiting...
In this paper, we will analyze the depth factor in general monocular video sequence. We can distinguish foreground from background without additional information and then create the binocular image by shifting foreground pixels. By applying CID method, we will get the strength of the sharpness and contrast from image by evaluating the farness of the region based on property of region color, and then...
In this paper, we propose a novel dynamic discrete framework to address image morphing with application to optical flow estimation. We reformulate the problem using a number of discrete displacements, and therefore the estimation of the morphing parameters becomes a tractable matching criteria independent combinatorial problem which is solved through the FastPD algorithm. In order to overcome the...
Accurate estimation of optical flow is a challenging task, which often requires addressing difficult energy optimization problems. To solve them, most top-performing methods rely on continuous optimization algorithms. The modeling accuracy of the energy in this case is often traded for its tractability. This is in contrast to the related problem of narrow-baseline stereo matching, where the top-performing...
Sparse features have traditionally been tracked from frame to frame independently of one another. We propose a framework in which features are tracked jointly. Combining ideas from Lucas-Kanade and Horn-Schunck, the estimated motion of a feature is influenced by the estimated motion of neighboring features. The approach also handles the problem of tracking edges in a unified way by estimating motion...
We present a method to fully automatically fit videos in 16:9 format on 4:3 screens and vice versa. It can be applied to arbitrary aspect ratios and can be used to make videos suitable for mobile viewing devices with small and possibly uncommonly sized displays. The cropping sequence is optimised over time to create smooth transitions and thus leads to an excellent viewing experience. Current televisions...
A key criticism for using a template/visual-model based object-tracker is that they often lack robustness to partial occlusions. This results from the global nature of the algorithm as opposed to operating on local features as in feature-based methods. Nevertheless, visual-model based methods could have significant advantage as they can model more complex objects and use more of the available data...
In this paper, we propose an efficient direct method that estimates pure translation motion parameters in dynamic scenes. We develop an algorithm that computes, directly, phase information in Fourier domain. The computations are locally performed and limited to small patches of the image. The local measurement of motion parameters are then combined in a more global interpretation by using parametric...
We propose real-time heterodyne imaging interferometry using the three-phase correlation image sensor (3PCIS). The 3PCIS produces temporal correlation between incident light intensity and three-phase reference signals at each pixel and outputs the results as images in every frame. This property enables simultaneous demodulation of amplitude and phase images of heterodyne interference within a single...
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