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.
An important task in computer vision is object localization and recognition within images and video. Achieving real-time object localization and recognition on low-power devices is especially relevant in the context of wearable technologies. Indeed, wearable devices have a reduced size and cost and limited computational power leading to a challenging scenario for classical computer vision algorithms...
Texture classification is an essential task in computer vision that aims at grouping instances that have a similar repetitive pattern into one group. Detecting texture primitives can be used to discriminate between materials of different types. The process of detecting prominent features from the texture instances represents a cornerstone step in texture classification. Moreover, building a good model...
This paper presents a popular method called boosted hog features to detect pedestrians and vehicles in static images. We compared the differences and similarities of detecting pedestrians and vehicles, then we selected boosted hog features to get an satisfying result. In the part of detecting pedestrians, Histograms of Oriented Gradients (HOG) feature is applied as the basic feature due to its good...
The mismatch between the training data and the test data distributions is a challenging issue while designing many practical computer vision systems. In this paper, we propose a domain adaptation technique to tackle this issue. We are interested in a domain adaptation scenario where source domain has large amount of labeled examples and the target domain has large amount of unlabeled examples. We...
Embedded visual assist systems are emerging as increasingly viable tools for aiding visually impaired persons in their day-to-day life activities. Novel wearable devices with imaging capabilities will be uniquely positioned to assist visually impaired in activities such as grocery shopping. However, supporting such time-sensitive applications on embedded platforms requires an intelligent trade-off...
Object recognition is a very important task in the field of computer vision. We present a new method for object recognition. The image content is described by the image gradient. Then, the intersection distance is proposed to measure the similarities of the images of different objects. Our method demonstrates good performances on three face data sets.
This paper presents cross-database evaluations of automatic appearance-based gender recognition methodology using normalized raw pixels and SVM classifier under unconstrained settings. Proposed method uses both histogram specification and feature space normalization on automatically aligned faces to achieve reliable recognition rate for real scenarios. Using a web based unconstrained training database,...
Despite the existence of many state-of-the-art face verification systems, the use of complex features and/or high order recognition models in these systems limits their application in devices with low computation power or low latency requirement. In this paper, we approach the problem by performing verification using simple linear distance model. We introduce a novel probability-based distance metric...
This paper presents a Convolutional Neural Network (CNN) for document image classification. In particular, document image classes are defined by the structural similarity. Previous approaches rely on hand-crafted features for capturing structural information. In contrast, we propose to learn features from raw image pixels using CNN. The use of CNN is motivated by the the hierarchical nature of document...
To understand the human action in still images, it is effective to detect the human region. However, since appearance of human is much different due to pose and occlusion, the detection is quite difficult. Here we propose robust human detection method to pose and occlusion using Bag-of-Words (BoW). In general, the location information is helpful in classification. When the human has occlusion and...
Classifier fusion methods are usually used to combine multiple classification decisions and generate better classification results than any single classifier. In order to improve object classification accuracy, it is a common method to assign weights to classifiers based on their importance in a multiple decision system. In this paper we put forward a method to weight different classifiers in classifier...
In this paper, a semi autonomous robot design serves the purpose of automatic loading and unloading of blocks using Image processing and machine learning. The automation part includes automatically detecting the distance and loading/unloading of the load object. The robot undergoes semi unsupervised learning. Distance, is measured using single camera based on pixel area measurement. A G.U.I is present...
Automatic facial point detection plays arguably the most important role in face analysis. Several methods have been proposed which reported their results on databases of both constrained and unconstrained conditions. Most of these databases provide annotations with different mark-ups and in some cases the are problems related to the accuracy of the fiducial points. The aforementioned issues as well...
The amber gemstones classification system is proposed and described in this paper. The amber data used in experiments are collected by amber art craft industry experts and divided manually into 30 classes. The presented investigations were care out in order to find out most accurate and fast classifier for online amber sorting application. QDA, KNN, RBF, and decision tree classifiers were tested....
Automatic object recognition in digital satellite images is not a simple task due to several variations present in the capture process and object appearance and pose, consequently, different general purpose techniques have been proposed. In this paper, an approach with LBP boosted cascade classifier for automatic runway detection in high resolution satellite imagery is analyzed. Promising results...
Human Computer Interaction takes the attention of many researches all over the world, researches try to invent more natural and intuitive interaction ways between humans and computers. However, people depend mainly on their hands to interact with surrounding objects in everyday life. In this paper we present a novel appearance based method to recognize and track human hand in an unknown environment...
This paper presents an approach to detect moving and static objects occurring in a video by a novel model-based tracking. The method exploits the spatial and motion coherence of objects across image frames that results from the known bounded shape distortion and object's velocity between two consecutive frames. The interframe transformation space is thus reduced to a reasonable small space of only...
In order to have a rich representation for human action, we propose to combine two complementary features so that a human posture can be characterized in more details. In particular, the distance signal feature and the width feature are combined in an effective way to enhance each other's discriminating capability. The resulting feature vector is quantized into mid-level features using k-means clustering...
Date fruits are small fruits that are abundant and popular in the Middle East, and have growing international presence. There are many different types of dates, each with different features. Sorting of dates is a key process in the date industry, and can be a tedious job. In this paper, we present a method for automatic classification of date fruits based on computer vision and pattern recognition...
The Haar-like cascaded classifier has been used in license plate detection and yields a high detection rate, but it often has high false positives. We introduced a classifier which was trained through histogram of oriented gradients (HOG) features to judge the likelihood of candidate plates detected by Haar classifier, and selected the candidate with highest likelihood as the final plate, in order...
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.