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We address the problem of estimating and removing localized image blur, as it for example arises from moving objects in a scene, or when the depth of field is insufficient to sharply render all objects of interest. Unlike the case of camera shake, such blur changes abruptly at the object boundaries. To cope with this, we propose an automated sharp image recovery method that simultaneously determines...
This paper proposes a human detection method that combines range image segmentation and human detection based on image local features. The method uses a stereo vision system called Subtraction Stereo, which extracts a range image of foreground regions. An extracted range image is segmented for each object by Mean Shift Clustering. Human detection based on local features is applied to each segment...
In this paper, we propose a video deblurring method for recovering effectively the blurred video caused by camera shake. First, we estimate the blur kernel for each blurred video frame by introducing a preprocessing strategy which employs the anisotropic diffusion and shock filter to get strong edges from each video frame. Second, for video deblurring, we propose a temporal cubic rhombic mask technique,...
This paper addresses the problem of silhouette-based human action segmentation and recognition in monocular sequences. Motion History Images (MHIs), used as 2D templates, capture motion information by encoding where and when motion occurred in the images. Inspired by codebook approaches for object and scene categorization, we first construct a codebook of temporal motion templates by clustering all...
The use of low-cost devices for depth estimation, such as Microsoft Kinect, is becoming more and more popular in computer vision research. In this paper, we propose an algorithm for background modeling which exploits this kind of devices to make the background and foreground models more robust to effects such as camouflage and illumination changes. Our algorithm, after a preprocessing stage for aligning...
Person re-identification aims to match people across non-overlapping camera views, which is an important and challenging task. In order to obtain a robust metric for measuring (dis)similarities of (un)matched image pairs, metric learning has been introduced recently. Most existing works focus on seeking a Mahalanobis distance by employing sparse pair wise (dis)similarity constraints. However, the...
Motion blurred images are widely existing when using a hand-held camera especially under the dim lighting conditions. Since edge information contained in the noisy image may be blurred by the motion blur, a blurred/noisy image pair captured under different exposure time can help to restore a sharp image. In the traditional deblurring methods based on blurred/noisy image pair, the deblurring process...
Video stabilization enhances video quality by stabilizing unstable motion. This paper proposes a new video stabilization method that simultaneously factors and smooths motion trajectories. We model the trajectories with a time-variant local subspace constraint. Every column of the trajectory matrix is factored and smoothed in separate local subspace. This model makes our method more flexible and accurate...
We propose a novel unified framework for the initial detection of possible targets within the aerial images using saliency detection. Our method is a bottom-up approach and computes Locally Adaptive Regression Kernel (LARK) from the given image, which measures the likeness of a pixel to its surroundings. Visual saliency is then computed using the self-resemblance measure. The framework results in...
This paper studies a system of video surveillance based on ARM, which detects mobile objects dynamically, whose purpose is to protect the safety of special places. It uses the S3C2416 processor as the core of the whole system to design circuit and software; and it uses open source program to detect whether there is an object is moving dynamically or not; it will alarm and automatically capture images...
In this paper we present a biologically inspired rotationally-invariant end-to-end recognition system demonstrated in hardware with a bitmap camera and a Field Programmable Gate Array (FPGA). The system integrates the Ripple Pond Network (RPN), a neural network that performs image transformation from two dimensions to one dimensional rotationally invariant temporal patterns (TPs), and the Synaptic...
In this paper we present a new approach for monocular image based lane border detection in situations where the characteristics of the pavement and the lane border are unknown. To achieve real time performance on standard hardware we analyze statistical characteristics of 1D signals on certain profile lines to find different types of features which belong to the lane border. These features are used...
This paper presents a novel directionally adaptive cubic-spline interpolation method which is applicable to mobile camera digital zoom systems. The problems of conventional (linear and cubic-spline) and advanced interpolation exhibit blurring and jagging artifacts in the digitally zoomed image. To solve this problem, the proposed method performs directionally adaptive interpolation using the optimal...
We propose an efficient algorithm for motion deblurring with kernel estimation using consecutive images. First we estimate motion vectors between consecutive images using optical flow and RANSAC. Then we calculate the weights of motion vectors. The proposed method is similar to Ben-Ezra's method. The main difference is that we use a single camera for estimating a blur kernel and capturing a blurred...
Automatic gender classification of an individual can be very useful in video-based surveillance systems and human-computer interaction systems. In this paper, we propose an approach to integrate information from multi-view gait at the feature level. First, gait energy images (GEI) are constructed from the video streams for different viewpoints. Then, the feature fusion is performed by putting GEI...
In this paper, we propose a simple, novel plane sweep technique for refocusing plenoptic images. Rays are projected directly from the raw plenoptic image captured on the sensor into the output image plane, without computing intermediate representations such as subaperture views or epipolar images. Interpolation is performed in the output image plane using splatting. The splat kernel for each ray is...
Defocus blur is an indicator for the depth structure of a scene. However, given a single input image from a conventional camera one cannot distinguish between blurred objects lying in front or behind the focal plane, as they may be subject to exactly the same amount of blur. In this paper we address this limitation by exploiting coded apertures. Previous work in this area focuses on setups where the...
In this paper, we attack the problem of learning a predictive model of a depth camera and manipulator directly from raw execution traces. While the problem of learning manipulator models from visual and proprioceptive data has been addressed before, existing techniques often rely on assumptions about the structure of the robot or tracked features in observation space. We make no such assumptions....
A monocular visual servo system for a target with variable shape has been developed in this paper. It consists of two parts: an image-processing unit and a servo control unit. For the image-processing unit, the motion between the target and image center is determined by a template match approach. The image is grabbed by a video camera equipped on a pan-tilt robot and the robot is controlled to track...
Camera shake is a well-known source of degradation in digital images, as it introduces motion blur. Taking satisfactory photos under dim lighting conditions or using a hand-held camera is challenging. Same problems arise when camera is connected to mechanical equipments, that transfer vibrations to the camera itself. Since decades, many different theories and algorithms have been proposed with the...
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