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.
With suggested computational post-processing workflow for correcting optical distortions, the Fresnel lens can finally be used in lightweight and inexpensive computer vision sensors. Common methods for image enhancement do not comprehensively address the blurring artifacts caused by strong chromatic aberrations in images produced by a simple Fresnel optical system. To deliver image quality acceptable...
A genetic programming (GP)-based framework to learn the effective feature representation for image dehazing is proposed in this work. In GP, an individual program is randomly generated and genetically evolved to achieve the desired goal. To make GP estimate haze in an input image, a set of operators and operands is designed, each of which is a primitive of a GP program. Specifically, we provide four...
The particle size distribution (PSD) of a dispersed phase is a fundamental geometrical characteristic that needs to be determined from digital images for many industrial processes involving a multiphase flow. Nevertheless, when dealing with 2-D images, only the projections of the particles are visualized and therefore the particles can overlap each other. In this way, this paper aims to develop and...
We construct a robust and precise multi-orientation text detection system in scene images which can extensively locate possible characters with multi-information fusion. In our method, an adaptive multi-channel character grouping algorithm is first proposed to extract all possible character candidates robustly, and an AdaBoost classifier is then to properly identify character candidates as characters...
We propose a machine learning based approach to real-time detection and classification assistance for images from unknown environments. While systems for detecting and classifying regular structures like faces in still images are well established, the task of e. g. detecting new morphotypes/objects in an environment is much more complex. The morphotypes/objects are not guaranteed to have apriori known...
This paper presents a method for detecting a pedestrian by leveraging multi-spectral image pairs. Our approach is based on the observation that a multi-spectral image, especially far-infrared (FIR) image, enables us to overcome inherent limitations for pedestrian detection under challenging circumstances, such as even dark environments. For that task, multi-spectral color-FIR image pairs are used...
This paper deals with automatic image colorization. This is a very difficult task, since it is an ill-posed problem that usually requires user intervention to achieve high quality. A fully automatic approach is proposed that is able to produce realistic colorization of an input grayscale image. Motivated by the recent success of deep learning techniques in image processing, we propose a feed-forward,...
This paper presents fine-tuned CNN features for person re-identification. Recently, features extracted from top layers of pre-trained Convolutional Neural Network (CNN) on a large annotated dataset, e.g., ImageNet, have been proven to be strong off-the-shelf descriptors for various recognition tasks. However, large disparity among the pre-trained task, i.e., ImageNet classification, and the target...
Computational visual aesthetics has recently become an active research area. Existing state-of-art methods formulate this as a binary classification task where a given image is predicted to be beautiful or not. In many applications such as image retrieval and enhancement, it is more important to rank images based on their aesthetic quality instead of binary-categorizing them. Furthermore, in such...
Computer-Aided Diagnosis (CAD) has witnessed a rapid growth over the past decade, providing a variety of automated tools for the analysis of medical images. In surgical pathology, such tools enhance the diagnosing capabilities of pathologists by allowing them to review and diagnose a larger number of cases daily. Geared towards developing such tools, the main goal of this paper is to identify useful...
In this paper, we propose a saliency detection model for RGB-D images based on the contrasting features of color and depth within a Bayesian framework. The depth feature map is extracted based on superpixel contrast computation with spatial priors. We model the depth saliency map by approximating the density of depth-based contrast features using a Gaussian distribution. Similar to the depth saliency...
the objective of this work is to compute the Time-to-Collision (TTC) of surrounding vehicles of a vehicle using motion information in driving video. The key advantage in this work is the extraction of potential danger without vehicle detection and recognition in prior, but directly from the motion divergence in the video. We analyze the trace expansion both horizontally and vertically condensed in...
In this paper, we present a method for vision-based place recognition in environments with a high content of similar features and that are prone to variations in illumination. The high similarity of features makes difficult the disambiguation between two different places. The novelty of our method relies on using the Bag of Words (BoW) approach to derive an image descriptor from a set of relevant...
Target tracking using color based appearance models is very popular in visual tracking. However, trackers based only on color are fragile and often drift to the background when it has similar appearances. In this paper, we propose an efficient way to use distinctive target colors to track the target and eliminate the drift problem. Colors are sampled from the target and its immediate surrounding region...
Manga (Japanese comics) are popular all over the world, and are created digitally. In this paper, we propose an interactive segmentation method tailored for manga. The proposed method enables annotators to select areas in manga efficiently. Our experimental results showed that the proposed framework works better than Adobe Photoshop CC, which is the most widely used commercial image editing software.
Background estimation can be regarded as a problem to construct the background from a series of video frames including moving objects in the scene. Scene background estimation is the essential prerequisite, or at least can be helpful for many applications such as video surveillance, video segmentation, and privacy protection for videos. To perform this task, in this paper we propose a robust framework...
This paper describes the evaluation of the Auto-Adaptive Parallel Neural Network Architecture, AAPNNA, in the SBMnet dataset. AAPNNA is an artificial neural model based on two networks whose neurons represent two different Background models that adapt their parameters at different rates. A very important feature of AAPNNA is its capacity to auto adapt to new scenario conditions as demonstrated with...
This paper describes iris biometric matching performed using the iris pictures captured by the standard visible spectrum smart phone cameras from the MICHE II database. Our method uses a combination of a popular iris code approach and a periocular biometric based on the Multi-Block Transitional Local Binary Patterns. The authentication scores are calculated separately, and the results are combined...
Surveillance cameras have become big business, with most metropolitan cities spending millions of dollars to watch residents, both from street corners, public transportation hubs, and body cameras on officials. Watching and processing the petabytes of streaming video is a daunting task, making automated and user assisted methods of searching and understanding videos critical to their success. Although...
Scene text detection and recognition have become active research topics in computer vision. In this paper, we focus on the detection of text proposal from wild images. Text proposals attempt to generate a relatively small set of bounding box proposals that are most likely to contain text. Different from previous methods that merge similar region based on property of individual region, we assumed that...
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.