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A variety of portable or wearable navigation systems mounted on smart glasses and smartphones have been developed to assist visually impaired people over the last decade. In these systems, collision detection is one of the key components. Many conventional methods with the monocular vision estimate the collision risk based on the motion information of obstacles in the image by measuring the size change...
Detection of multi-manipulated image has always been a more realistic direction for digital image forensic technologies, which extremely attracts interests of researchers. However, mutual affects of manipulations make it difficult to identify the process using existing single-manipulated detection methods. In this paper, a novel algorithm for detecting image manipulation history of blurring and sharpening...
In recent years, many vehicle detection algorithms have been proposed. However, a lot of challenges still remain. Local Binary Pattern (LBP) is one of the most popular texture descriptors which has shown its superiority in face recognition and pedestrian detection. But the original LBP pattern is sensitive to noise especially in flat region where gray levels change rarely. To solve this problem, Local...
Detecting pedestrians is a challenging problem owing to the motion of the subjects, the camera and the background and to variations in pose, appearance, clothing, illumination and background clutter. The Region Covariance Matrix (RCM) descriptors show experimentally significantly out-performs existing feature sets for pedestrian detection. In this paper, we present an efficient features extraction...
Many attempts have been made to identify the region of interest in an image. In this paper, we have provided a new approach for ROI detection using the output of image annotation. Our claim is that because ROI is a subjective concept, a method should be used to diagnosis human mental models and for this purpose, we have used KNN base annotation in our method. Because many people in pictures that are...
The images of lace textile are particularly difficult to be analyzed in digital form using classical image processing techniques. The major reasons of this difficulty emerge from the complex nature of lace which generally has different textures in its constituents like the background and patterns. In this paper, we study the behavior of Image Histogram (HistI) and Local Binary Patterns (LBP) on image...
Virtualized cloud environments have emerged as a necessity within modern unified ICT infrastructures and have established themselves as a reliable backbone for numerous always-on services. ‘Live’ intra-cloud virtual-machine (VM) migration is a widely used technique for efficient resource management employed within modern cloud infrastructures. Despite the benefits of such functionality, there are...
This paper presents a multiple feature fusion method using topic model for social image visualization. Images in social media are represented from several aspects such as their visual information and tags. The proposed method extracts low-level features from social images and their tags and calculates their integrated high-level features. Specifically, the proposed method applies multilayer multimodal...
Interest points matching for aerial visual odometry using quadrotor MAV is tackled in this work. First, a set of sparse feature points are extracted using ORB detector. These are then grouped using Gradient Vector Flow (GVF) fields by finding points of high symmetry within the image. A robust matching strategy is introduced to improve the motion estimation. In order to validate ORB features matches,...
The essence of 3D model retrieval is to classify and to sort. An algorithm based on neural network is proposed in this paper. After pretreatment, six projection viewpoints are selected to project the 3D model in order to generate six two-dimensional images. Then the images are transformed by Fourier Transform to obtain the vector features. Finally, the dimension of vector is compressed to input into...
In recent years, pedestrian detection for Automobile Driver Assistance System (ADAS) is a primordial task in the smart vehicle. Histogram of oriented gradients (HoG) is one of the most effective pedestrian feature extraction approaches to the study. In this paper, an optimization of pedestrian detection based on HOG method is presented and investigated to achieve an accurate human detection system...
Face recognition and verification is still a challenging problem due to several issues such as pose, facial expression, occlusion, imaging conditions, rotation, size and orientation. This paper addresses the problem of recognizing human faces despite the presence in pose and size variation. To handle these problems, we mainly focus on block size definition. Instead of uniform block we thus propose...
We propose a novel framework for fast and robust video anomaly detection and localization in complicated crowd scenes. Images of each video are split into cells for extracting local motion features represented by optical flow. In the train videos, most background cells are subtracted by ViBe model. Feature vectors are extracted from each cell by integrating the value of optical flow in 8 different...
Image level fusion combines an image in different ways with its original version so that the combine image may contain more relevant information than the original one. This paper presents a novel method for face recognition by fusing original and corresponding diagonal images. Two ways of image fusion technique have been performed here. Firstly, we generate diagonal face image from original face image...
Gender classification of depth images is a challenging problem, most research work attempted to use shape information to solve this problem in the past literature. In this work, we propose a new fusion scheme for gender classification using both texture and shape features. A new ensemble scheme is advocated to combine texture and shape feature at the feature level. To evaluate the performance of our...
In text document clustering documents are represented as feature vectors where features can be either words or phrases. Documents can belong to different topics when categorized by humans; however it is noted that obtaining one to one mapping between the features and the topics is almost impossible since the same features can and will be used in documents in different topics. Such common features...
We propose a solution for efficiently transforming video data over a delay tolerant network. We extract and transport only relevant features from the video frame at a minimal computational cost using low cost COTS embedded environment.
In this paper, we propose a new method to detect abnormal behavior in crowd video. The motion influence matrix is proposed to represent crowd behaviors. It is generated based on concept of human perception with block-level motion vectors which describe actual crowd movement. Furthermore, a generalized framework is developed to detect abnormal crowd behavior using motion influence matrix. The proposed...
Pedestrian detection plays important roles in various applications such as automobile driving assistance and surveillance camera system. The co-occurrence histograms of oriented gradients (CoHOG) feature descriptor showed good performance since thirty co-occurrences at each pixel position represent various spatial characteristics of object shapes. Though extraction of co-occurrence histogram features...
In most action recognition tasks, the target videos are of different temporal length and an action may be repeated several times in one video. As a result, encoding the distribution of video feature points that are far away from each other or are detected from different occurrences of the action into the video representation is inappropriate. It is better that sub video shots containing different...
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