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This paper presents an automatic event detection system fusing low and mid level features for soccer videos. We first employ an improved approach for Shot Boundary Detection with color and our mean-gradient feature. Then we classify the shots into two view types. We also perform a template-based replay detection for each shot. Play-break sequences are then generated using a rule-based method. We devise...
Malaria is a serious global health problem. It requires fast and effective diagnosis for detecting and classifying the type of infection. Proper treatment should be administered in a timely fashion to prevent an outbreak. Microscopic examination of thick blood films is one of the current standards for malaria diagnosis. However, inspecting a thick blood film is time-consuming and requires experienced...
In this paper, we present, first, a new method for color feature extraction based on SURF detectors. Then, we proved its efficiency for flower image classification. Therefore, we described visual content of the flower images using compact and accurate descriptors. These features are combined and the learning process is performed using a multiple kernel framework with a SVM classifier. The proposed...
Two light beams that are seen as of having the same colour but that have different spectra are said to be metameric. The colour of a light beam is based on the reading of severel photodetectors with different spectral responses and metamerism results when a set of photodetectors is unable to resolve two spectra. The spectra are then said to be metameric. We are interested in exploring the concept...
This paper studies the problem of improving object recognition using the novel RGB-D data. To address the problem, a new convolutional Fisher Kernels (CFK) method is proposed to represent RGB-D objects powerfully yet efficiently. The core idea of our approach is to integrate the both advantages of the convolutional neural networks (CNN) and Fisher Kernel encoding (FK): CNN model is flexible to adapt...
This paper presents a method to estimate a depth map using an infrared projector and a pair of infrared color cameras that can capture infrared and color images simultaneously. The infrared projector projects a dot pattern so that the cameras capture infrared images of a scene textured by the dots with which depths to surfaces in the scene can be estimated regardless of whether they have visible textures...
The process of image tampering is nothing but digital process that needs the knowledge good visual creativity as well as image properties. There are different kinds of image tampering such as copy & move, splicing, resize, cropping etc. In this paper we are focusing on blurred image splicing. The image splicing is done for many reasons, the most critical impacts of image splicing related to security...
This paper presents a novel multikernel based Sparse representation for the classification of Remotely sensed images. The sparse representation based feature extraction are in a run which is a signal dependent feature extraction and thus more accurate. Multikernel Sparse representation was also had proved to be more accurate and less computationally complex while implemented in other applications...
In the last few years, many technologies for helping differently-abled people have been developed continually including technologies for recognising sign language that enables them to communicate with each other. In this research, we studied sign language recognition using Microsoft Kinect. Conventionally, Microsoft Kinect uses its depth sensor to collect depth and motion features in order to recognise...
The classical Camshift face tracking algorithm requires a higher environmental demand and is susceptible to the skin color interference. To solve the above problems, an improved Camshift tracking algorithm — ERC (Environmental Robust Camshift) is presented. Firstly, the RGB histogram equalization is applied in ERC to extend the hue differentiation between pixels; secondly, the statistical and spatial...
With the rising of intelligent vehicle technologies, traffic sign recognition become an essential problem in computer vision. Focusing on the traffic sign recognition under real-world scenario, this paper aims to develop novel local feature representation to improve the traffic sign recognition performance. Especially, with the local histogram feature as a basic unit, a novel histogram intersection...
Place recognition is the frond-end of Simultaneous Localization and Mapping (SLAM). Topological representations depend on good association of vertices, which ultimately depends on the front-end. In this paper, we consider a robot lost in an unknown environment trying to construct a topological map to localize itself using a laser range finder and odometry information. The algorithm makes use of an...
Robust fingertip force detection from fingernail image is a critical strategy that can be applied in many areas. However, prior research fixed many variables that influence the finger color change. This paper analyzes the effect of the finger joint on the force detection in order to deal with the constrained finger position setting. A force estimator method is designed: a model to predict the fingertip...
To deal with the poor stability of tracking infrared target by using the gray-level features in traditional methods, a novel method is provided for tracking target in infrared based on color image fusion. Firstly, This method uses the color transfer technology to achieve the color fusion image for the infrared target. On the basis of the color image, the color histogram is established by kernel function...
Process scheduling algorithm plays a crucial role in operating system performance and so does the data-structure used for its implementation. A scheduler is designed to ensure the distribution of resources among the tasks is fair along with maximization of CPU utilization. The Completely Fair Scheduler (CFS), the default scheduler of Linux (since kernel version 2.6.23), ensures equal opportunity among...
To print ceaseless tone images, Electrophotographic printers mostly use halftoning method. Scanned pictures procured from such hard transcripts are generally wrecked by screen like antiquities. Recently an approach for reviving relentless image from scanned halftone picture was accomplished. This new model considers both printing deformities and halftone motifs. At first denoising computation is proposed...
We propose the technique of the semi-automatic image creation. By this we mean an automatic completion of an image that is partially defined on the given domain. The essential feature of this technique is that the complementary area is much larger than that where the image is defined. Moreover, the proposed technique can be used in image upsampling, image inpainting, etc. In this contribution, we...
Chromatic aberration, caused by photographic lens imperfections, results in the image of only one spectral channel being sharp, while the other channels are blurred depending on their wavelengths difference with the sharp channel. We study chromatic aberration for a system that jointly records color and near-infrared (NIR) images on a single sensor. Chromatic aberration in such a system leads to a...
Image classification is currently a vital and challenging topic in computer vision. Although it has been achieved many classification algorithms so far, the classification of natural images still remains great difficulties in image processing. In this paper, we propose a semantic linear-time graph kernel for image classification. Each image is represented by a graph and the vertex of each graph corresponds...
In this work we describe a Convolutional Neural Network (CNN) to accurately predict the scene illumination. Taking image patches as input, the CNN works in the spatial domain without using hand-crafted features that are employed by most previous methods. The network consists of one convolutional layer with max pooling, one fully connected layer and three output nodes. Within the network structure,...
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