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In this paper, we propose using 3D Convolutional Neural Networks for large scale user-independent continuous gesture recognition. We have trained an end-to-end deep network for continuous gesture recognition (jointly learning both the feature representation and the classifier). The network performs three-dimensional (i.e. space-time) convolutions to extract features related to both the appearance...
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...
A novel approach for fast iris recognition on mobile devices is presented in this paper. Its key features are: (i) the use of a combination of classifiers exploiting the iris colour and texture information; (ii) its limited computational time, particularly suitable for fast identity checking on mobile devices; (iii) the high parallelism of the code, making this approach also appropriate for identity...
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...
This paper describes the AcTiVComp: detection and recognition of Arabic Text in Video competition in conjunction with the 23rd International Conference on Pattern Recognition (ICPR). The main objective of this competition is to evaluate the performance of participants' algorithms to automatically locate and/or recognize overlay text lines in Arabic video frames using the freely available AcTiV dataset...
Active one-shot scanning techniques have been widely used for various applications. Stereo-based active one-shot scanning embeds a positional information regarding the image plane of a projector onto a projected pattern to retrieve correspondences entirely from a captured image. Many combinations of patterns and decoding algorithms for active one-shot scanning have been proposed. If the capturing...
3D-point set registration is an active area of research in computer vision. In recent years, probabilistic registration approaches have demonstrated superior performance for many challenging applications. Generally, these probabilistic approaches rely on the spatial distribution of the 3D-points, and only recently color information has been integrated into such a framework, significantly improving...
In multiview image stitching, the colors of images in a scene might vary when images are taken under different illumination or camera settings. A common way to produce a seamless stitched image is to transform the colors of a target image to match that of a source image. In this paper we present a color transfer method based on two premises: first, pixels in the generated image should have similar...
Reliable object discovery in realistic indoor scenes is a necessity for many computer vision and service robot applications. In these scenes, semantic segmentation methods have made huge advances in recent years. Such methods can provide useful prior information for object discovery by removing false positives and by delineating object boundaries. We propose a novel method that combines bottom-up...
Traffic panels contain rich text and symbolic information for transportation and scene understanding. Fast detection of traffic panels facilitates text information extraction but has been paid little attention by the community. In this paper, we propose a fast and robust approach for rectangular traffic panel detection from traffic scene images. Considering the rectangular shape of traffic panels,...
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 presents a text detection method based on multi-scale Stroke Width Transform (SWT). First, an image pyramid is built and SWT is performed on each level of the pyramid. Second, edge components are filtered using two novel features, stroke pair ratio (SPR) and edge density of a connected component (EDC). Next, the remaining edge components on each level are grouped into text lines. And these...
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...
Template matching is a technique for finding a part of reference image which matches a template image. This paper presents a new fast template matching algorithm which can detect the most similar position. In the proposed method, first, an effective initial threshold is calculated using Winner Update Algorithm. Next, very fast template matching is achieved by using this initial threshold in Multilevel...
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...
The existing quaternion-type moments (QTMs) are based on the quaternion representation (QR) of color images. However, this representation creates redundancy when using four-dimensional quaternions to represent color images with three components. In this paper, for RGB-D images, the QR is improved by combining both color and depth information, which is invariant to lighting and color variations. The...
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...
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...
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