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Visual tracking is a significant but challenging field in computer vision. Although considerable progress has been made in recent years, robust tracking in complicated scenes remains an open problem. Trackers get confused easily when similar objects appear or heavy clutter occurs due to indistinguishable features. In this work, a more effective feature extraction method based on convolutional neural...
Can we train the computer to beat experienced traders for financial assert trading? In this paper, we try to address this challenge by introducing a recurrent deep neural network (NN) for real-time financial signal representation and trading. Our model is inspired by two biological-related learning concepts of deep learning (DL) and reinforcement learning (RL). In the framework, the DL part automatically...
Traffic Sign Recognition (TSR) system is a significant component of Intelligent Transport System (ITS) as traffic signs assist the drivers to drive more safely and efficiently. This paper represents a new approach for TSR system using hybrid features formed by two robust features descriptors, named Histogram Oriented Gradient(HOG) features and Speeded Up Robust Features(SURF) and artificial neural...
Traffic Sign Recognition (TSR) system is a vital component of intelligent transport system. It plays an important role by enhancing the safety of the drivers, pedestrians and vehicles as traffic signs provide important information of the traffic environment of the road and assist the drivers to drive more safely and easily by guiding and warning. This paper represents road sign detection and recognition...
A challenging research issue, which has recently attracted a lot of attention, is the incorporation of emotion recognition technology in serious games applications, in order to improve the quality of interaction and enhance the gaming experience. To this end, in this paper, we present an emotion recognition methodology that utilizes information extracted from multimodal fusion analysis to identify...
Roadside vegetation classification has recently attracted increasing attention, due to its significance in applications such as vegetation growth management and fire hazard identification. Existing studies primarily focus on learning visible feature based classifiers or invisible feature based thresholds, which often suffer from a generalization problem to new data. This paper proposes an approach...
Detection of lung abnormalities by characterizing lung sounds has been a primary step for clinical examination for a pulmonologist. This work focuses on utilization of cepstral features for lung sound analysis and classification. The proposed method incorporates statistical properties of cepstral features along with artificial neural network (ANN) based classification. Experimental results indicate...
In this paper, we propose an efficient image stitching using structure deformation. We use image stitching based on common stitching algorithms such as speeded up robust features (SURF) feature detection, approximated nearest neighbor (ANN) matching and random sample consensus (RANSAC) parameter estimation. And we use homography similarity to identify if input images have enough correlation. To reduce...
Fast and robust traffic sign recognition is very important but difficult for the safety driving assist systems. This study addresses the fast and robust traffic sign recognition to enhance safety driving. We first adopt the typical Hough transform methods to implement coarse-grained locating of the candidate regions (shapes of rectangle, triangle and circle, etc.) of the traffic signs; and then propose...
Most of the state-of-the-art methods for action recognition are very complex and variant to the geometric transformation like scaling, translation and rotation. Cuboid based method required all frames to extract the cuboid of action that's why cuboid based methods are expensive. Other methods use contour based approach for feature representation which is not robust to noise. So we require a very fast...
This paper reports the development of a software suite to be accessed in future with any General Packet Radio Service (GPRS) or High Speed Packet Access (HSPA) enabled mobile phone or Personal Digital Assistant (PDA) for the extraction and analysis of disease-related features from the photograph of paper based ECG records. In India and other developing countries, the cheaper paper based ECG machines...
Recognizing characters in a scene helps us obtain useful information. For the purpose, character recognition methods are required to recognize characters of various sizes, various rotation angles and complex layout on complex background. In this paper, we propose a character recognition method using local features having several desirable properties. The novelty of the proposed method is to take into...
Camera-based computer vision technology is able to assist visually impaired people to automatically recognize banknotes. A good banknote recognition algorithm for blind or visually impaired people should have the following features: 1) 100% accuracy, and 2) robustness to various conditions in different environments and occlusions. Most existing algorithms of banknote recognition are limited to work...
In this paper, we present a new key generation model for image hashing using neural network, which does not embed any data into the content but is able to extract meaningful data from target image. This model trains artificial neural network to assign predefined code and uses this trained artificial neural network weight and the coordinates of the selected feature sub blocks of target image as keys...
Due to a wide spectrum of applications, autonomous ground vehicle navigation based on visual information has rapidly developed in the past decade. These applications include intelligence transportation systems, military robots and mars/lunar robot rovers. However, most of the attention was focused on navigating the robot in day light environment using visual spectrum images captured from CCD cameras...
This study focuses on the design of an intelligent machine vision and sorting system. The vision system uses an artificial neural network trained to perform recognition. A Bluetooth communication link facilitates communication between the intelligent recognition system and a robot control computer. Image feature vectors are transmitted to the remote control computer for recognition and a robot control...
This paper presents a novel local-feature-based algorithm to track objects through frames. Real-time performance and occlusion are great challenges in object tracking. Local features are more distinctive than global features in dealing with occlusion. SURF (Speeded-Up Robust Feature) can robustly identify objects in clutter scene and occlusion. However, initial SURF algorithm has difficulty in matching...
In order to solve the problem of robustly classifying underwater multiple targets in shallow sea, a novel classification method based on Multidimensional Scaling (MDS) is proposed. This algorithm extracts the robust and distinct feature difference between targets by means of MDS, and optimizes the feature distance by combining with kernel function. A modified K-means classifier is utilized to cluster...
Due to no damage to original data, the lossless watermarking is more suitable for copyright protection of vector maps. In this paper, a lossless watermarking scheme based on the global characteristics of vector map is proposed. It begins with feature point extraction of each polyline, based on which, for the extracted feature points and non-feature points, the scheme utilizes the relation model established...
HVS theory plays important role in the application of digital image watermarking technique. When inserting watermarking, the visual masking feature of HVS could be fully used to design digital watermarking algorithm with good perceived performance. When extracting watermarking from the damaged image, human's visual feature could be combined to recover the damaged image so as to obtain better effect...
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