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Cost aggregation is one of the popular method for stereo matching due to efficiency and effectiveness. Their limitation is a high complexity and some error near the contour, which makes them not to implement in real time. Furthermore, the weakness makes them unattractive for many applications which require the accurate depth information. In this paper, we present a cost aggregation method using the...
We propose an estimation method of initial labels based on scale-invariant feature transform (SIFT), high dimensional color transform (HDCT), and machine learning for propagation-based saliency detection. The label propagation strategy is efficient for saliency detection, but its accuracy depends on the distribution of initial labels. In this paper, the proposed method respectively estimates initial...
Autonomous on-road vehicles or vision-based driver assistance benefit from free-space analysis. This paper evaluates the accuracy of free-space detection in stereo and monocular vision on KITTI benchmark data. Such an evaluation of low-level computer vision algorithms is, for example, also necessary as free-space analysis is recently becoming an important module for designing vehicle test beds. The...
The generalized linear model (GLM), where a random vector x is observed through a noisy, possibly nonlinear, function of a linear transform output z = Ax, arises in a range of applications such as robust regression, binary classification, quantized compressed sensing, phase retrieval, photon-limited imaging, and inference from neural spike trains. When A is large and i.i.d. Gaussian, the generalized...
We consider the problem of recovering an image using block compressed sensing (BCS). Traditional BCS algorithms recovers each image block independently and utilizes post-processing methods for removing the blocking artifacts. In contrast, we propose an image recovery method free of post-processing, where we utilize a lapped transform (LT) for the sparse representation of the image in order to reduce...
In this paper, we accomplish simultaneous localization and mapping using the monocular LSD-SLAM. This method is different with feature method, estimating the accurate and reconstructing the large scale environment map. Using the direct image alignment, the environment can be mapped in pose-graph of key frames semi-dense maps. The LSD-SLAM contains two advantage. A novel direct tracking method can...
This paper revisits the problem of joint estimation of activity and attenuation from non-TOF PET data. Two methods are described to generate non-identifiable activity images, which are not uniquely determined by their attenuated 2D non-TOF PET data if the attenuation is unknown. The results show that non-identifiability is the generic case and is not limited to the examples of radially symmetric objects,...
For wireless remote access security, forensics, electronic commerce and surveillance applications, there is a growing need for biometric speaker identification systems to be robust to noise. This paper examines the robustness issue for the case of additive white noise at signal to noise ratios ranging from 0 to 30 dB. A Gaussian mixture model classifier based on adaptation of a universal background...
The Gamma-Gamma (G-G) distribution which is one of the most important distributions has been introduced to model the irradiance. One famous study has relied on a method of moment technique involving fractional moments to estimate the parameters of the G-G distribution. The mean square error of these parameter estimates is large in cases where the Rytov variance is small or the true distribution of...
The restoration of motion-blurred image is one of important subjects of image restoration. This paper mainly researched on the restoration methods for motion-blurred image based on estimated motion blurring angle and motion blurring length. First, the motion blurring angle is estimated by Hough transform algorithm. In order to reduce the impact of concrete structure on the detection, the edge detection...
For multi-sensor data fusion applications the accurate alignment of different sensor data is essential for the proper combination of matching features. In food inspection system the boxing often is in a rectangular shape. This knowledge can be used to rectify the image data, an important step in the alignment stage. In case of low contrast between boxing and background, the detected contour may differ...
Estimating complex spectra is a widespread operation in signal processing and in some applications a high dynamic range, which requires low sidelobe levels, is essential. For data with uniform sample spacing, weightings are commonly applied to Fourier transforms to suppress sidelobes, increasing dynamic range at the cost of some loss of spectral resolution. However, if a significant proportion of...
Depth estimation of the surrounding environment using a stereoscopic camera setup is an important and fundamental research topic in computer vision. Due to its running time and quality performance in real situations the semi global matching algorithm is often used. The biggest disadvantage of the semi global approach is its large memory footprint. On the other hand, block matching stereo is leaner...
A Speaker Localization algorithm based on Neural Networks for multi-room domestic scenarios is proposed in this paper. The approach is fully data-driven and employs a Neural Network fed by GCC-PHAT (Generalized Cross Correlation Phase Transform) Patterns, calculated by means of the microphone signals, to determine the speaker position in the room under analysis. In particular, we deal with a multi-room...
Vision is the most important sense for humans and because of this human vision system we are able to see the 3D world around us with great clarity and are able to find out depth of each and every object. Many Active and Passive depth estimation techniques have been proposed which are capable of estimating depth of real world scene among which one of the passive method, stereo vision has been proven...
Structure tensor analysis on epipolar plane images (EPIs) is a successful approach to estimate disparity from a light field, i.e. a dense set of multi-view images. However, the disparity range allowable for the light field is limited, because the estimation becomes less accurate as the range of disparities become larger. To overcome this limitation, we propose a new method called sheared EPI analysis,...
Haze removal, which is also referred to as image dehazing, has been extensively used to improve the visibility in images captured under inclement weather. In particular, the dark channel prior (DCP)-based single image dehazing has received the greatest amount of interest due to its superior performance. However, since the DCP is based on the characteristics of natural outdoor images, its reliability...
Information is at the center of decision making in many systems and use-cases. In cooperative or hostile environments, agents communicate their subjective opinions about various phenomenon. However, sources of these opinions are not always competent and honest but often erroneous or even malicious. Furthermore, malicious sources may adopt certain behaviors to mislead the decision maker in a specific...
There is a tiny difference between the main peak and side peaks after the traditional quadratic correlation calculation in the time-delay estimation of passive acoustic positioning system. It is easy to lead to a wrong peak value when the system resolution is low or mutations caused by noises occur near the side peaks. In order to weaken the influence of the quadratic correlation side peaks, the method...
In recent years, the Unmanned Aerial Vehicles (UAVs) technologies are widely employed in many fields such as disaster monitoring, map revision, and aerial imagery. A UAV aerial remote sensing system has several advantages such as low cost, high spatial resolution, and flexibility. However, one single UAV image can only cover a small area due to the limited altitude of the vehicle and the restricted...
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