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Matching specific persons across scenes, known as person re-identification, is an important yet unsolved computer vision problem. Feature representation and metric learning are two fundamental factors in person re-identification. However, current person re-identification methods, which use single handcrafted feature with corresponding metric, could be not powerful enough when facing illumination,...
This paper proposes a novel model for contrast enhancement of RGB images. The average local contrast measure is increased within a variational framework which preserves the hue of the original image by coupling the channels. The user is enabled to intuitively control the level of the contrast as well as the scale of the enhanced details. Moreover, our model avoids large modifications of the original...
On the problem of tracking objects in videos, a recent and distinguished approach combining tracking and detection methods is the TLD framework. The detector identifies the object by its supposedly confirmed appearances. The tracker inserts new appearances into the model using apparent motion. Their outcomes are integrated by using the same similarity metric of the detector which, in our point of...
In this paper, we propose a robust video colorization method automatically through limited color references in a video sequence. The proposed method first estimates motion vectors between a monochrome frame and colored reference frames for initial matching by optical flow. Then it transfers color information to matched points in the monochrome frame and further propagates color information of matched...
In this work we introduce a variational nonconvex model for color image regularization. We express the variational problem as an instance of the half quadratic algorithm (HQA). Moreover, the generalized HQA allows us to prove convergence of the variational problem. As a demonstrator of our framework, we consider a vectorial total variation (VTV) formulation with an additional nonconvex pair-wise color-channel...
It is well known that many more than three or four spectral measurements are required for accurate measurement of color. Previous work has shown seven to ten measurements can yield accurate results on average, but with significant numbers of errors above the threshold of obvious visual detection. Furthermore, the filters used for these measurements are very difficult to fabricate. We show that such...
This paper proposes a new depth image recovery algorithm which recovers a high resolution depth image using RGB color image from a very low resolution depth image. In order to achieve a high recovery performance, this paper represents the high resolution depth image as the sum of an average distance image and a surface image. Experimental examples show that the proposed algorithm achieves a high resolution...
We address the problem of full body human pose estimation in video. Most previous work consider body part, pose or trajectory of body part as basic unit to compose the pose sequence. In contrast, we consider tracklet of body part as the basic unit. Based on this medium granularity representation we develop a spatio-temporal graphical model to select an optimal tracklet for each part in each video...
In this paper we introduce a novel decolorization strategy built on image fusion principles. Decolorization (color-to-grayscale), is an important transformation used in many monochrome image processing applications. We demonstrate that aside from color spatial distribution, local information plays an important role in maintaining the discriminability of the image conversion. Our strategy blends the...
In this paper, we propose an algorithm to remove rain streaks from single color image. Firstly, the guided filter, cooperated with rain pixels detection are used to separate a color image into low-frequency and high-frequency parts so that most rain components exist in the high-frequency part. Then, we focus on the high-frequency part to extract the non-rain details according to the characteristics...
This paper presents a novel variational image inpainting method to solve the problem of generating, from 3-D lidar measures, a dense depth map coherent with a given color image, tackling visibility issues. When projecting the lidar point cloud onto the image plane, we generally obtain a sparse depth map, due to undersampling. Moreover, lidar and image sensor positions generally differ during acquisition,...
Although non-local image denoising has attracted much research effort due to its superior performance, little attention has focused on its color extension. Most existing non-local color image denoising methods process the color channels of an input image separately. However, in order to improve the performance of color image denoising, all color channels should be processed jointly for fully utilizing...
The transition to High Dynamic Range (HDR) requires new standards for video. Existing standards for SDR have tacitly assumed the CRT's native response characteristics for the Electro-Optical Transfer Function or EOTF, often referred to as ‘gamma’. Since the EOTF was universal and fixed by the physics of the CRT, SDR standards have been typically expressed in terms of the complementary Opto-Electrical...
In this paper, we propose an image segmentation-based algorithm to perform upsampling of noisy low-resolution depth maps using information from the high-resolution color image. The depth map is initially upscaled using standard image interpolation technique, and then refined by a process based on the combination of Normalized Cuts segmentation and various smoothness priors in order to obtain a high...
Bilateral filtering is a commonly used technique in image processing. However, being nonlinear, it is computationally expensive. The situation gets worse while the filter radius grows up. Several works have been proposed to accelerate the computation. Nevertheless, most techniques are tailored for grayscale image bilateral filtering or confined to specific kernel functions. In this paper, we propose...
A spectral clustering based video object segmentation technique is proposed in this work. A foreground separation model is introduced which uses thresholding by different features to produce an initial labeling for each frame of the input sequence. We use a combination of color, optical flow, spatial-coordinates, spatiotemporal saliency and the initial foreground labeling to construct an interframe...
The problem of person re-identification, identifying the same person appeared in different camera views, is an important and challenging task in computer vision that has high potential application in areas like visual surveillance. In this paper we introduce a new feature fusion strategy for person reidentification that combines low-level Weighted Histograms of Overlapping Stripes (WHOS) features...
Catadioptric cameras developed recently provide images with large field of view. Nevertheless, due to the use of mirrors, these images contain significant radial distortions that are necessary to handle when processing them. In this paper, we present the use of differential geometry for the construction of a hybrid structure tensor suited to the multicomponent catadioptric images. This structure tensor...
Graph-Based Representation (GBR) has recently been proposed for rectified multiview dataset. The core idea of GBR is to use graphs for describing the color and geometry information of a multiview dataset. The color information is represented by the vertices of the graph while the scene geometry is represented by the edges of the graph. In this paper, we generalize the GBR to multi-view images with...
Video databases, used for benchmarking and evaluating the performance of new video technologies, should represent the full breadth of consumer video content. The parameterisation of video databases using low-level features has proven to be an effective way of quantifying the diversity within a database. However, without a comprehensive understanding of the importance and relative frequency and of...
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