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.
Human action classification is an important task in computer vision. The Bag-of-Words model uses spatio-temporal features assigned to visual words of a vocabulary and some classification algorithm to attain this goal. In this work we have studied the effect of reducing the vocabulary size using a video word ranking method. We have applied this method to the KTH dataset to obtain a vocabulary with...
This paper analyzes and compares the rate-accuracy and rate energy characteristics of various video rate adaptation techniques in computer vision applications. The analyzed rate adaptation techniques include spatial, spatial with up scaling, temporal, and Signal-to-Noise Ratio (SNR). We experiment with standard video sequences as well as 300 security, surveillance, news, and speech videos. These videos...
Nanomaterial has demonstrated its advantages in a variety of application fields such as biosensors and next-generation computer chips. It is important yet challenging to precisely capture and recover the morphological characteristics of nanomaterial for nanomanufacturing quality control. We propose a computer vision-assisted approach in this paper to recover the structural details of nanowires and...
Falls are a major threat to the independence and quality of life of elderly people. As the worldwide population of elderly increases each year, responding to falls is essential. Computer vision systems provide a new promising solution in responding falls through detecting fall events. This paper presents a new technique in detecting falls based on human shape variation. The proposed visual based fall...
The mean field (MF) methods are an energy optimization method for Markov random fields (MRFs). These methods, which have their root in solid state physics, estimate the marginal density of each site of an MRF graph by iterative computation, similarly to loopy belief propagation (LBP). It appears that, being shadowed by LBP, the MF methods have not been seriously considered in the computer vision community...
In this paper we will try to present a new technique of navigation in a virtual environment using dynamic gestures performed with arms and we made a performance analysis of the navigation system. System evaluation has been made using following performance parameters: accuracy, precision and sensitivity of gesture recognition.
The study of efficient image representations has attracted significant interest due to the computational needs of large-scale applications. In this paper we study the performance of the recently proposed VLAD method for aggregating local image descriptors when combined with SURF features, in the domain of image search. The experiments show that when SURF features are used as local image descriptors,...
Building a photorealistic, 3D model of an object or a complete scene from image-based methods is a fundamental problem in computer vision, and has many applications in robotic perception, navigation, exploration and mapping. In this paper, we extend current state-of-the-art in the computation of depth maps by presenting an accurate and computationally efficient iterative hierarchical algorithm for...
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...
In this paper, we present a novel and computationally efficient pruning technique to speed up the Shi-Tomasi and Harris corner detectors. The proposed technique quickly prunes non-corners and selects a small corner candidate set by approximating the complex corner measure of Shi-Tomasi and Harris. The actual corner measure is then applied only to the reduced candidate set. Experimental results on...
High-level vision applications often incorporate image segmentation techniques into their preprocessing stages to reduce image data and to improve overall execution efficiency. Traditional segmentation approaches often focus on creating homogenous, connected regions of pixels to roughly correspond with image object boundaries. These methods tend to blend or remove important image details and are often...
An extensive amount of research is being undertaken to gracefully solve the Human action recognition problem. To this end, in this paper, we introduce the application of self- similarity surfaces for human action recognition. These surfaces were introduced by Shechtman & Irani (CVPR'07) in the context of matching similarities between images or videos. These surfaces are obtained by matching a...
In this paper, we propose a novel stereo matching algorithm based on disparity propagation using cellular evolutionary neural networks (CEN). Most of previous works have drawbacks and advantages in accuracy, running time and scene types of image; however, our advantage is obtaining not exceedingly-high but satisfactory accuracy for various scenes with low computational cost. Our algorithm calculates...
Classifier combination can be used to combine multiple classification decisions to improve object classification performance, and weighted average is a popular method for this purpose. In this paper we propose to use a graph-theoretic clustering method to define the weights for SVM classifier decisions. Specifically, we use the dominant set clustering to evaluate the difficulty of a kernel matrix...
Pedestrian detection is an important task in many applications such as intelligent transportation systems, image retrieval, surveillance systems, automated personal assistance, etc. This paper proposes a set of modified Haar-like features that have parallelogram shapes. Using the proposed feature descriptors to develop a rapid detection system for pedestrian detection based on decision tree structure...
We introduce a novel subspace segmentation method called Minimal Squared Frobenius Norm Representation (MSFNR). MSFNR performs data clustering by solving a convex optimization problem. We theoretically prove that in the noiseless case, MSFNR is equivalent to the classical Factorization approach and always classifies data correctly. In the noisy case, we show that on both synthetic and real-word datasets,...
Superpixel segmentation has become a popular preprocessing step in computer vision with a great variety of existing algorithms. Almost all algorithms claim to compute compact superpixels, but no one showed how to measure compactness and no one investigated the implications. In this paper, we propose a novel metric to measure superpixel compactness. With this metric, we show that there is a trade-off...
This paper presents a comparative study of different classification methodologies for the task of fine-art genre classification. 2-level comparative study is performed for this classification problem. 1st level reviews the performance of discriminative vs. generative models while 2nd level touches the features aspect of the paintings and compares semantic-level features vs low-level and intermediate...
Pedestrian detection problem has been a touchstone of various image feature descriptors. In this paper, we evaluate four kinds of representative local descriptors (HOG, Haar-like, SURF and LBP) for pedestrian representation. Our goal is to find out the best combination of feature descriptors by analyzing and evaluating the complementarities of them. With the cross validation method, we first find...
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.