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Traffic light detection (TLD) is a vital part of both intelligent vehicles and driving assistance systems (DAS). General for most TLDs is that they are evaluated on small and private datasets making it hard to determine the exact performance of a given method. In this paper we apply the state-of-the-art, real-time object detection system You Only Look Once, (YOLO) on the public LISA Traffic Light...
The principal focus of this study was to assess the feasibility of an experimental technique capable to detect the superficial defects that might be present on the surface of the composite panels fabricated through high volume manufacturing technologies, such as sheet moulding compound (SMC). The preliminary investigations performed suggest that reasonable similarities exist between numerical and...
Metal detectors are widely used to detect and localize land mines, as well as metallic clutter that causes many false alarms. These false alarms are handled by manual inspection with a prodder or using extra features like size and depth as well as fusion with other sensors like ground penetrating radar or chemical sensors. Directly shape itself has never been used, mainly due to infeasibility of the...
This paper presents a novel appearance and shape feature, RISAS, which is robust to viewpoint, illumination, scale and rotation variations. RISAS consists of a keypoint detector and a feature descriptor both of which utilise texture and geometric information present in the appearance and shape channels. A novel response function based on the surface normals is used in combination with the Harris corner...
Can we reconstruct the entire internal shape of a room if all we can directly observe is a small portion of one internal wall, presumably through a window in the room? While conventional wisdom may indicate that this is not possible, motivated by recent work on ‘looking around corners’, we show that one can exploit light echoes to reconstruct the internal shape of hidden rooms. Existing techniques...
The problem of object localization in image appear ubiquitously in computer vision applications including image classification, object detection and visual tracking. Recently, it is shown that multiple-instance learning(MIL) which is regarded as the fourth machine learning framework compared with supervised learning, unsupervised learning and reinforce learning has been verified that will get good...
In this paper, we propose a digital restoration algorithm dealing with a one of the most common defect in archived video so-called blotches. TWo main modules compose the algorithm: blotches detection and removal. For the first module, we propose efficient blotches detection algorithm based on spatio-temporal information. This is done by using a temporal median filter applied on the adjacent frames...
Image registration which is frequently required in Medical, Computer vision and remote sensing field is used to align two images geometrically. This paper presents efficient method for providing speedup and more accuracy in compared to current state of the art existing methods. This paper focuses on Feature detection using Harris detector which gives best result based on performance and has firm invariance...
Retinal vessel keypoint detection and classification is a fundamental step in tracking the physiological changes that occur in the retina which is linked to various retinal and systemic diseases. In this paper, we propose a novel Vessel Keypoint Detector (VKD) which is derived from the projection of log-polar transformed binary patches around vessel points. VKD is used to design a two stage solution...
Computational technology advancements have enabled the radar engineers to model and understand extended targets. One of the common statistical models of extended target is based on Gaussian distribution. In this paper, we address the problem of detection of such an extended target that has a non-Gaussian clutter plus noise background using MIMO radar. Specifically, approximations are sought for theoretically...
The process of mining includes various methodologies and data classification is one of the advantageous methods involved in it. It not only eases the process of machine learning but also gives a platform for proper functioning of the process. There are cases wherein the data which is important or unidentified is missed during the process of classification. The process of mining is highly affected...
Regularized Tyler Estimator's (RTE) have raised attention over the past years due to their attractive performance over a wide range of noise distributions and their natural robustness to outliers. Developing adaptive methods for the selection of the regularisation parameter α is currently an active topic of research. Indeed, the bias-performance compromise of RTEs highly depends on the considered...
There is considerable interest in obtaining a low-cost mathematical description, which describes the interaction between a low frequency alternating magnetic field and a conducting object. Electrical engineers have proposed that the voltage perturbation in a coil placed in the field can be described in terms of a tensor that characterises its shape and material properties. In previous work [4], [6],...
Instance based human segmentation works on various parameters like labeling of an image at pixel level, partitioning it into distinct instances and the background of the image. The localization, identification and extraction of human image with reliable appearance in a surveillance video are a widely used applications now days. Due to the strong changes in foreground and background and irregularly...
Recently, the system for closely-spaced tag management (at 13.56 MHz) and the system for the long distance identification (at 920 MHz) have been carried out to practical use. For continuous logistics, it is desired that those are integrated seamlessly. However, integration into the system, which uses the frequency band of 13.56 MHz, is disadvantageous to keep the feature of the long distance identification...
Face Feature Point Detection (FFPD) is a significant and interesting topic in many related areas of face recognition. A new face mesh model is presented in this paper to realize the FFPD in a fast and training-free approach. At first, an automatic face mesh initialization algorithm based on the detection of face, eye-pairs and mouth is proposed. Second, a local operator referred as Edge Attractor...
A novel similarity-covariant feature detector that extracts points whose neighborhoods, when treated as a 3D intensity surface, have a saddle-like intensity profile. The saddle condition is verified efficiently by intensity comparisons on two concentric rings that must have exactly two dark-to-bright and two bright-to-dark transitions satisfying certain geometric constraints. Experiments show that...
We extend earlier work by Essick et al. [1,2] with a study of similarities among sky localization maps corresponding to gravitational-wave transients. Earlier in 2016, the Advanced Laser Interferometer Gravitational-wave Observatory (LIGO) announced the first direct observation of gravitational waves from binary black holes [3,4]. Motivated by the fact that multiple detection and localization algorithms...
In this paper, a method for unknown object tracking in output images from 360-degree cameras called Modified Training-Learning-Detection (MTLD) is presented. The proposed method is based on the recently introduced Training-Learning-Detection (TLD) scheme in the literature. The flaws of the TLD approach have been detected and significant modifications are proposed to enhance and to elaborate the scheme...
Traffic panels contain rich text and symbolic information for transportation and scene understanding. Fast detection of traffic panels facilitates text information extraction but has been paid little attention by the community. In this paper, we propose a fast and robust approach for rectangular traffic panel detection from traffic scene images. Considering the rectangular shape of traffic panels,...
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