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Nowadays, digital story is for the most part around the place. Images noticeably are such of the virtually important categories bounded by the accessible data. Image processing is a way of doing thing to interpret an thought into digital comprise and plow some operations on it, in term to win an enhanced brain wave or to dig in to the past some enjoyable reference from it. Image Processing forms essential...
Viewpoint quality estimation methods allow the determination of the most informative position in a scene. However, a single position usually cannot represent an entire scene, requiring instead a set of several viewpoints. Measuring the quality of such a set of views, however, is not trivial, and the computation of an optimal set of views is an NP-hard problem. Therefore, in this work, we propose three...
The manual adjustment of travel speed to cover medium or large distances in virtual environments may increase cognitive load, and manual travel at high speeds can lead to cybersickness due to inaccurate steering. In this work, we present an approach to quickly pass regions where the environment does not change much, using automated suggestions based on the computation of common visibility. In a user...
Abstract—In this paper, we analyse the use of Convolutional Neural Networks (CNNs or ConvNets) to discriminate vegetation species with few labelled samples. To the best of our knowledge, this is the first work dedicated to the investigation of the use of deep features in such task. The experimental evaluation demonstrate that deep features significantly outperform wellknown feature extraction techniques...
We have analyzed the problems associated with matching regions among the pair of images over the large set of overlapping regions. It is being studied that, matching images by using regions having unstructured association can be a serious problem. In this research we propose a linear formulation technique, which is matching simultaneously, so that the matched area can have color similarity histogram,...
Human action recognition from videos has wide applicability and receives significant interests. In this work, to better identify spatio-temporal characteristics, we propose a novel 3D extension of Gradient Location and Orientation Histograms, which provides discriminative local features representing not only the gradient orientation, but also their relative locations. We further propose a human action...
Segmentation of TV news broadcast into semantically meaningful stories is an essential pre-requisite for a wide range of video analytics applications. In this work we have introduced a hybrid approach for news story segmentation based on conditional random fields (CRFs). The story boundary detection problem is converted into a shot classification problem by classifying video shots into either of the...
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...
This paper considers the offline signature verification problem which is considered to be an important research line in the field of pattern recognition. In this work we propose hybrid features that consider the local features and their global statistics in the signature image. This has been done by creating a vocabulary of histogram of oriented gradients (HOGs). We impose weights on these local features...
A fragile watermark provides an effective solution to ascertain the integrity of an image. However, security of the watermark is endangered during transmission through an unsecured network. This paper aims to secure watermark by applying fuzzy model based invertible transformation to the cover image after embedding visual watermark into it. The controlled non-linear transformation permutes the watermark...
In this article, a novel technique about secure medical information transmission of patient inside medical cover image is presented by concealing data using decision tree concept. Decision tree shows a robust mechanism by providing decisions for secret information concealing location in medical carrier image using secret information mapping concept. RSA encryption algorithm is being used for patient's...
We introduce a novel bags-of-features framework based on relative position descriptors, modeling both spatial relations and shape information between the pairwise structural subparts of objects. First, we propose a hierarchical approach for the decomposition of complex objects into structural subparts, as well as their description using the concept of Force Histogram Decomposition (FHD). Then, an...
This paper investigates the effects of sampling on action recognition performance. Currently, dense (regular grid) sampling and uniform random sampling are popular strategies that achieve state-of-the-art performance. However, they are data-blind and pay equal attention to locations of different informativeness. In this paper, a Shannon information based adaptive sampling approach is proposed for...
Deep learning-based models have recently been widely successful at outperforming traditional approaches in several computer vision applications such as image classification, object recognition and action recognition. However, those models are not naturally designed to learn structural information that can be important to tasks such as human pose estimation and structured semantic interpretation of...
Person re-identification is a fundamental challenging task in Computer Vision that consists on recognizing the same person across multiple potentially non-overlapping cameras. This importance is due to the important challenges that it proposes like pose, background clutter and occlusion, illumination changes and low resolution. Also, most of the existing approaches rely on brute-force matching between...
Generalized Hough transform, when applied to object detection, recognition and pose estimation, can be susceptible to spurious voting depending on the Hough space to be used and hypotheses to be voted. This often necessitates additional computational steps like non-maxima suppression and geometric consistency checks, which can be costly and prevent voting based methods from being precise and scalable...
Automatic summarization of streaming news images is critical for efficient news browsing. Although image duplicates are redundant for news reading, the number of duplicates of a news image is a good indicator for its importance. We describe the architecture used in a news aggregation system for online streaming news image summarization. Given a sequence of images for a news topic, we first cluster...
We present a novel technique for pollen identification from sets of multifocal image sequences obtained from optical microscopy. Our algorithm analyzes the visual texture of pollen grains for each focal image, and performs identification using a fast sequence-matching algorithm. Although we develop a pollen-recognition protocol, the method is applicable to other microscopy object-recognition tasks...
With the huge amount of web video data and its exponential growth in recent years, there are new challenges in Near-Duplicate Video Detection (NDVD) which have attracted much attention owing to its wide applications. One of the problems is how to extract discriminative features to achieve higher precision, and the other problem is how to improve the efficiency of large scale video analysis. Existing...
Reversible data hiding is a kind of information hiding technique that can exactly recover the original image through data hiding and extraction. It can be potentially used in the medical and military applications. In the literature, by using the maximum inter-class square error to separate the background and foreground, the principal gray-scale values in the segmented background can be identified...
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