Image moments have been widely used for designing robust shape descriptors that are invariant to rigid transformations. In this work, we address the problem of estimating non-rigid deformation fields based on image mo...
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Image feature detection is a fundamental issue in computervision. SIFT[1] and SURF[2] are very effective in scale-space feature detection, but their stabilities are not good enough because unstable features such as e...
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ISBN:
(纸本)9783642123030
Image feature detection is a fundamental issue in computervision. SIFT[1] and SURF[2] are very effective in scale-space feature detection, but their stabilities are not good enough because unstable features such as edges are often detected even if they use edge suppression as a post-treatment. Inspired by Harris function[3], we extend Harris to scale-space and propose a novel method - Harris-like Scale Invariant Feature Detector (HLSIFD). Different to Harris-Laplace which is a hybrid method of Harris and Laplace, HLSIFD uses Hessian Matrix which is proved to be more stable in scale-space than Harris matrix. Unlike other methods suppressing edges in a sudden way(SIFT) or ignoring it(SURF), HLSIFD suppresses edges smoothly and uniformly, so fewer fake points are detected by HLSIFD. the approach is evaluated on public databases and in real scenes. Compared to the state of arts feature detectors: SIFT and SURF, HLSIFD shows high performance of HLSIFD.
Pose estimation of people have had great progress in recent years but so far research has dealt with single persons. In this paper we address some of the challenges that arise when doing pose estimation of interacting...
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this paper presents a systematic Differential Fault Analysis (DFA) method on Feistel ciphers, the outcome of which closely links to that of the theoretical cryptanalysis with provable security. For this purpose, we in...
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Previous efforts in eye gaze tracking either did not consider head motion, or considered the 6 DOF head motions with multiple cameras or light sources. In this paper, we show that it is possible to track eye gaze unde...
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ISBN:
(纸本)9783642123030
Previous efforts in eye gaze tracking either did not consider head motion, or considered the 6 DOF head motions with multiple cameras or light sources. In this paper, we show that it is possible to track eye gaze under naturally head rotations(Yaw and Pitch) with only an ordinary webcam. We first carry out a study to examine the occurrence of eye-head coordination, and then show how to track such coordinated gaze by deriving a linear coordination equation and developing a tracking system based on a single webcam. Besides the theoretical aspect, we develop a vision-based tracking framework that can achieve an acceptable tracking accuracy in our experiments for estimating such eye-head coordinated gaze.
the detection of motion boundaries has been and remains a longstanding challenge in computervision. In this paper, the recovery of motion boundaries is recast in a broader scope, as focus is placed on the more genera...
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ISBN:
(纸本)9783642123030
the detection of motion boundaries has been and remains a longstanding challenge in computervision. In this paper, the recovery of motion boundaries is recast in a broader scope, as focus is placed on the more general problem of detecting spacetime structure boundaries, where motion boundaries constitute a special case. this recasting allows uniform consideration of boundaries between a wider class of spacetime patterns than previously considered in the literature, both coherent motion as well as additional dynamic patterns. Examples of dynamic patterns beyond standard motion that are encompassed by the proposed approach include, flicker, transparency and various dynamic textures (e.g., scintillation). Toward this end, a novel representation and method for detecting these boundaries in raw image sequence data are presented. Central to the representation is the description of oriented spacetime structure in a distributed manner. Empirical evaluation of the proposed boundary detector on challenging natural imagery suggests its efficacy.
Research on the motion perception has received great attention in recent years. In this paper, on the basis of existing biological vision achievement, a computer implementation is carried out to examine the performanc...
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ISBN:
(纸本)9783642133176
Research on the motion perception has received great attention in recent years. In this paper, on the basis of existing biological vision achievement, a computer implementation is carried out to examine the performance of the biologically-motivated method for motion detection. the proposed implementation is validated in both synthetic and real-world image sequences. the experimental comparisons with a representative gradient optical flow solution show that the biological correlation detector has better robustness and anti-noise capability.
this paper proposes a self-created multi-layer cascaded architecture for multi-view face detection. Instead of using predefined a priori about face views, the system automatically divides the face sample space using t...
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ISBN:
(纸本)9783642123030
this paper proposes a self-created multi-layer cascaded architecture for multi-view face detection. Instead of using predefined a priori about face views, the system automatically divides the face sample space using the kernel-based branching competitive learning (KBCL) network at different discriminative resolutions. To improve the detection efficiency, a coarse-to-fine search mechanism is involved in the procedure, where the boosted mirror pair of points (MPP) classifiers is employed to classify image blocks at different discriminatory levels. the boosted MPP classifiers can approximate the performance of the standard support vector machines in a hierarchical way, which allows background blocks to be excluded quickly by simple classifiers and the 'face like' parts remained to be judged by more complicate classifiers. Experimental results show that our system provides a high detection rate with a particularly low level of false positives.
Analyzing the crowd dynamics from video sequences is an open challenge in computervision. Under a high crowd density assumption, we characterize the dynamics of the crowd flow by two related information: velocity and...
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ISBN:
(纸本)9783642123030
Analyzing the crowd dynamics from video sequences is an open challenge in computervision. Under a high crowd density assumption, we characterize the dynamics of the crowd flow by two related information: velocity and a disturbance potential which accounts for several elements likely to disturb the flow (the density of pedestrians, their interactions withthe flow and the environment). the aim of this paper to simultaneously estimate from a sequence of crowded images those two quantities. While the velocity of the flow can be observed directly from the images with traditional techniques, this disturbance potential is far more trickier to estimate. We propose here to couple, through optimal control theory, a dynamical crowd evolution model with observations from the image sequence in order to estimate at the same time those two quantities from a video sequence. For this purpose, we derive a new and original continuum formulation of the crowd dynamics which appears to be well adapted to dense crowd video sequences. We demonstrate the efficiency of our approach on both synthetic and real crowd videos.
In this paper, a two-stage scheme for the recognition of Persian handwritten isolated characters is proposed. In the first stage, similar shaped characters are categorized into groups and as a result, 8 groups are obt...
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