The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In today world the necessity for the autonomous mobile robots and vehicles is increasing. The safety autonomous moving demands the reliable and fast detection algorithms. The Histogram of Oriented Gradients (HOG) descriptors show significantly outperforms the existing feature sets for a human detection. Though the given method has a lot of type I errors. The amount of these errors can be decreased...
Density estimation is a fundamental part of statistical analysis and data mining. In high-dimensional domains, parametric methods and the commonly used non-parametric methods like histograms or Kernel estimators fail to perform properly. In this paper, we present computationally efficient data structures for efficient implementation of the Bayesian sequential partitioning (BSP), as a framework for...
This paper proposes a modified spatially-constrained similarity measure (mSCSM) method for endosomal structure detection and localization under the bag-of-words (BoW) framework. To our best knowledge, the proposed mSCSM is the first method for fully automatic detection and localization of complex subcellular compartments like endosomes. Essentially, a new similarity score and a novel two-stage output...
The problem of image enhancement for low-contrast images with the small-size objects is considered. The histogram-based method for contrast enhancement of low-contrast images with the small-size objects on the basis of the estimation of parameters of contrast distribution at boundaries of image elements for the various definitions of contrast kernels is proposed. The proposed method is intended for...
Saliency detection is a fundamental problem in computational and cognitive sciences. Nowadays, graph-based methods are widely applied to saliency detection including manifold ranking(MR) method, which is shown to be fast and effective. However, because of only using a single feature and imperfect selection strategy for background seeds, MR has a poor performance in some circumstances. In order to...
The given work describes a new technique of image segmentation, in particular for building detection on radar or infrared Earth-observation images. The method is based on property of most man-made objects which consist in straight edges and mostly right angles. The developed 2D adaptive image filter assists to detect straight edges even if given image fragment has a low contrast and has been extremely...
Axial proton density (PD) weighted magnetic resonance (MR) images of shoulder which has the ability to represent bone edema while preserving anatomical details, provides valuable information for the evaluation of traumatized shoulder. The low signal to noise ratio of PD weighted slices of MRI while being a powerful tool for the detection of the pathological conditions, can hamper the determination...
In this study, facial expression recognition is defined as a pair matching problem. Our objectives to formulate this talk in this way are to be able to decide whether the facial expressions of the unlabeled images of two people are the same or different and to benefit from the proposed pair matching methods that have been studied for many years in the face recognition field. The Extended Cohn-Kanade...
Local binary pattern (LBP) has limitation in extracting the edge and direction information, which is vital to infrared face recognition. A new infrared face recognition algorithm fusion of LBP and histogram of oriented gradients (HOG) is proposed. First, LBP operator is adopted to extract the texture feature of an infrared face, and then the edge features of the original infrared face are extracted...
In this paper we propose a new method for scene representation and recognition based on the concept of Region Subspaces. Each image is pre-segmented into semantically meaningful regions and local features are extracted at different scales from each such region. The Region Subspaces are the low-dimensional linear subspaces calculated from the set of local features inside each region. We also define...
Superpixel based methods have recently shown success in scene segmentation and labeling. In scene labeling, a superpixel algorithm is used first to segment the image into visually consistent small regions; then several feature descriptors are computed and classification is performed for each superpixel. In this paper, Kernel Codebook Encoding (KCB) of superpixel features is proposed. In KCB feature...
Real face recognition is a challenging problem especially when face images are subject to distortions. This paper presents an approach to tackle partial occlusion distortions present in real face recognition using a single training sample per person. First, original images are partitioned into multiple blocks and Local Binary Patterns are applied as a local descriptor on each block separately. Then,...
This paper proposes the method of vehicle license plate recognition, which is essential in the field of intelligent transportation system. The purpose of the study is to present a simple and effective vehicle license plate detection and recognition using non-bling image de-blurring algorithm. The sharpness of the edges in an image is restored by the prior information on images. The blue kernel is...
In this paper, we propose a novel method for global abnormal events detection in crowded scenes. Each video is described as the set of overlapping space-time cubes. The histogram of optical flow orientation and motion magnitude are used as global feature descriptor to capture the motion magnitude and orientation of the normal and abnormal events. The motion-rich space-time cubes are selected to enhance...
In this paper, we propose a neural network based distance metric learning method for a better discrimination in the sequence-matching based keyword search (KWS). In this technique, we conduct a version of Dynamic Time Warping (DTW) based similarity search on the speaker independent posteriorgram space. With this, we aim to compensate for the scarcity of the resources and overcome the out-of-vocabulary...
Compressed domain human action recognition algorithms are extremely efficient, because they only require a partial decoding of the video bit stream. However, the question what exactly makes these algorithms decide for a particular action is still a mystery. In this paper, we present a general method, Layer-wise Relevance Propagation (LRP), to understand and interpret action recognition algorithms...
This paper presents an improved pedestrian tracking algorithm with image sequences acquired by surveillance cameras. This pedestrian tracking algorithm is based on mean shift algorithm, and it uses color histogram equalization to improve the original algorithm. The improved algorithm performs much better than the original algorithm in some situations. We use the CAVIAR project/IST 2001 37540 dataset...
Malicious software, referred to as malware, continues to grow in sophistication. Past proposals for malware detection have primarily focused on software-based detectors which are vulnerable to being compromised. Thus, recent work has proposed hardware-assisted malware detection. In this paper, we introduce a new framework for hardware-assisted malware detection based on monitoring and classifying...
This paper presents a finger-spelling recognition system focusing on Thai finger-spelling sign language, derived from the computer vision, using SVM. In this study, global and local features were extracted from input finger images. In order to develop the recognition system, 15 Thai alphabet characters were collected from five hand signers, totally 375 character pictures, in order to train the system...
The problem of image contrast enhancement was considered. The histogram-based method for image contrast enhancement in automatic mode on the basis of the contrast distribution function at the boundaries of image elements (objects and background) for the different definitions of contrast kernels is proposed. A comparison of the proposed and known histogram-based methods of image contrast enhancement...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.