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Robust estimation of linear structures such as edges and junction features in digital images is an important problem. In this paper, we use an adaptive robust structure tensor (ARST) method where the local adaptation process uses spatially varying adaptive Gaussian kernel that is initialized using the total least-squares structure tensor solution. An iterative scheme is designed with size, orientation,...
Video stabilization and mosaicking is an important task when a video stream of a large area, such as the video stream from a UAV or a blimp, is received. In this paper we propose a novel approach for video stabilization and mosaicking from shaky video streams. We present a feature-based real-time video mosaicking pipeline performing image alignment by combining feature point detector, descriptor,...
While Optical Character Recognition (OCR) can be considered as a solved problem, text detection and recognition in real scene images is still extremely challenging and remains an open problem. Due to the wide variety of text appearances in real scenes, such as variations in font, size, color, orientation, partial occlusions, different distortions and illumination conditions, current results of both...
We propose a framework for Threat Image Projection (TIP) in cargo transmission X-ray imagery. The method exploits the approximately multiplicative nature of X-ray imagery to extract a library of threat items. These items can then be projected into real cargo. We show using experimental data that there is no significant qualitative or quantitative difference between real threat images and TIP images...
Identifying and detecting the unknown abnormal sparse signal has become an important issue for distributed networks. In this paper, we proposed a new detection scheme based on convex optimization for wireless sensor networks. Under the Neyman-Pearson testing framework, the detection scheme first estimates the unknown signal by employing the convex optimization at the fusion center. Then the sensor...
This paper proposes three robust detection algorithms for locating the cutting line in an image captured by a panel-cutting system. All of the proposed methods contain two stages: edge detection and line fitting. In this paper, edge detection can search interest gradients depending on the intensity concentration. Meanwhile, the proposed line-fitting algorithm is able to precisely fit a line by minimizing...
Authors proved existence of uniformly most powerful invariant algorithm based on the t-test. Conducted study allowed to synthesize decision rule for detection of image features on 3×3 pixel patch was found. Simulation proved stability of the proposed feature point detection algorithm to change of mean value and standard deviation of background pixels' intensity. Versatility of detection algorithm...
Robust face detection is one of the most important preprocessing steps to support facial expression analysis, facial landmarking, face recognition, pose estimation, building of 3D facial models, etc. Although this topic has been intensely studied for decades, it is still challenging due to numerous variants of face images in real-world scenarios. In this paper, we present a novel approach named Multiple...
In Cognitive Radio (CR), secondary radios are allowed to use the spectrum allocated to primary radios (PR) only if the spectrum is sensed to be unused by the PR users. Cooperative spectrum sensing is a sensing methodology in which secondary users send their detection results to a central fusion node for global decision. It has been shown that for single node detection, SNR wall provides a hard threshold...
A two stages car detection method using deformable part models with composite feature sets (DPM/CF) is proposed to recognize cars of various types and from multiple viewing angles. In the first stage, a HOG template is matched to detect the bounding box of the entire car of a certain type and viewed from a certain angle (called a t/a pair), which yields a region of interest (ROI). In the second stage,...
In this work we study the problem of weakly supervised human body detection under difficult poses (e.g., multiview and/or arbitrary poses) within the framework of multi-instance learning (MIL). We first point out the existence of the so-called “vanishing gradient” problem in MIL with a noisy-or rule as its bagging model. This is mainly due to the independence assumption of the noisy-or rule, which...
Starting from an object's location in a video frame, tracking-by-detection methods find the location of that object in a subsequent video frame. The tracker's detection step may produce multiple false positives during short-term occlusions, which can result in loss of track. We propose a tracking-by-detection method that is robust to short-term occlusions and false positives. Here, we extend the Struck...
Linear barcodes are the principal labeling system for retail products. Barcode reader apps found on smartphones always assume that the localization and framing of the barcode is performed manually by a sighted human operator. This is problematic for visually-impaired people since they don't know where to position the camera to scan the barcode. To solve this problem we propose a hand-free interface...
Object recognition based on local features computed at multiple locations is robust to occlusions, strong viewpoint changes and object deformations. These features should be repeatable, precise and distinctive. We present an operator for repeatable feature detection on depth images (relative to 3D models) as well as 2D intensity images. The proposed detector is based on estimating the curviness saliency...
The Ground Penetrating Radar (GPR) consists in an electromagnetic signal which is transmitted at different positions through the ground in order to obtain an image of the subsoil. In particular, the GPR is used to detect buried objects like pipes. Their detection and localisation are intricate for three main reasons. First, the noise is important in the resulting image due to the presence of several...
Many image processing applications require to detect a known pattern buried under noise. While maximum correlation can be implemented efficiently using fast Fourier transforms, detection criteria that are robust to the presence of outliers are typically slower by several orders of magnitude. We derive the general expression of a robust detection criterion based on the theory of locally optimal detectors...
Neural-machine interface (NMI) decoding errors challenge the clinical value of neural control of powered artificial legs, because these errors can dangerously disturb the user's walking balance, cause stumbles or falls, and thus threaten the user's confidence and safety in prosthesis use. Although extensive research efforts have been made to minimize the NMI decoding error rate, none of the current...
The shallow underwater acoustic channel offers a challenging environment. Besides long delay spreads caused by multiple surface-bottom reflections, the channel is time variant as well. In tropical waters, the problem is compounded further by impulsive noise created by snapping shrimp. Conventionally, the noise process is modeled by white impulsive noise. However, in reality, snapping shrimp noise...
At the last decades, face analysis remains a challenging research topic in the computer vision area. Beyond the visible band, infrared images had shown several advantages for face detection and recognition. From the proposed approaches for analyzing these images, the local analysis is recognized by its feasibility to overcome typical undesirable conditions such as noise, illumination, and affine transformations...
Adaptive tracking-by-detection is a popular approach to track arbitrary objects in various situations. Such approaches treat tracking as a classification task and constantly update the object model. The update procedure requires a set of labeled examples, where samples are collected from the last observation, and then labeled. However, these intermediate steps typically follow a set of heuristic rules...
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