Search results for "ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION"
showing 10 items of 982 documents
Exploiting Visual Saliency Algorithms for Object-Based Attention: A New Color and Scale-Based Approach
2017
Visual Saliency aims to detect the most important regions of an image from a perceptual point of view. More in detail, the goal of Visual Saliency is to build a Saliency Map revealing the salient subset of a given image by analyzing bottom-up and top-down factors of Visual Attention. In this paper we proposed a new method for Saliency detection based on colour and scale analysis, extending our previous work based on SIFT spatial density inspection. We conducted several experiments to study the relationships between saliency methods and the object attention processes and we collected experimental data by tracking the eye movements of thirty viewers in the first three seconds of observation o…
Texture classification for content-based image retrieval
2002
An original approach to texture-based classification of regions, for image indexing and retrieval, is presented. The system addresses automatic macro-textured ROI detection, and classification: we focus our attention on those objects that can be characterized by a texture as a whole, like trees, flowers, walls, clouds, and so on. The proposed architecture is based on the computation of the /spl lambda/ vector from each selected region, and classification of this feature by means of a pool of suitably trained support vector machines (SVM). This approach is an extension of the one previously developed by some of the authors to classify image regions on the basis of the geometrical shape of th…
A tool to support the creation of datasets of tampered videos
2015
Digital Video Forensics is getting a growing interest from the Multimedia research community, as the need for methods to validate the authenticity of a video content is increasing with the number of videos freely available to the digital users. Unlike Digital Image Forensics, to our knowledge, there are not standard datasets to test video forgery detection techniques. In this paper we present a new tool to support the users in creating datasets of tampered videos. We furthermore present our own dataset and we discuss some remarks about how to create forgeries difficult to be detected by an observer, to the naked eye.
State of the art in passive digital image forgery detection: copy-move image forgery
2017
Authenticating digital images is increasingly becoming important because digital images carry important information and due to their use in different areas such as courts of law as essential pieces of evidence. Nowadays, authenticating digital images is difficult because manipulating them has become easy as a result of powerful image processing software and human knowledge. The importance and relevance of digital image forensics has attracted various researchers to establish different techniques for detection in image forensics. The core category of image forensics is passive image forgery detection. One of the most important passive forgeries that affect the originality of the image is cop…
Fast adaptive frame preprocessing for 3D reconstruction
2015
Abstract: This paper presents a new online preprocessing strategy to detect and discard ongoing bad frames in video sequences. These include frames where an accurate localization between corresponding points is difficult, such as for blurred frames, or which do not provide relevant information with respect to the previous frames in terms of texture, image contrast and non-flat areas. Unlike keyframe selectors and deblurring methods, the proposed approach is a fast preprocessing working on a simple gradient statistic, that does not require to compute complex time-consuming image processing, such as the computation of image feature keypoints, previous poses and 3D structure, or to know a prio…
Path Modeling and Retrieval in Distributed Video Surveillance Databases
2012
We propose a framework for querying a distributed database of video surveillance data in order to retrieve a set of likely paths of a person moving in the area under surveillance. In our framework, each camera of the surveillance system locally pro- cesses the data and stores video sequences in a storage unit and the metadata for each detected person in the distributed database. A pedestrian’s path is formulated as a dynamic Bayesian network (DBN) to model the dependencies between subsequent observa- tions of the person as he makes his way through the camera net- work. We propose a tool by which the analyst can pose queries about where a certain person appeared while moving in the site duri…
HarrisZ$^+$: Harris Corner Selection for Next-Gen Image Matching Pipelines
2022
Due to its role in many computer vision tasks, image matching has been subjected to an active investigation by researchers, which has lead to better and more discriminant feature descriptors and to more robust matching strategies, also thanks to the advent of the deep learning and the increased computational power of the modern hardware. Despite of these achievements, the keypoint extraction process at the base of the image matching pipeline has not seen equivalent progresses. This paper presents HarrisZ$^+$, an upgrade to the HarrisZ corner detector, optimized to synergically take advance of the recent improvements of the other steps of the image matching pipeline. HarrisZ$^+$ does not onl…
Why you trust in visual saliency
2015
Image understanding is a simple task for a human observer. Visual attention is automatically pointed to interesting regions by a natural objective stimulus in a first step and by prior knowledge in a second step. Saliency maps try to simulate human response and use actual eye-movements measurements as ground truth. An interesting question is: how much corruption in a digital image can affect saliency detection respect to the original image? One of the contributions of this work is to compare the performances of standard approaches with respect to different type of image corruptions and different threshold values on saliency maps. If the corruption can be estimated and/or the threshold is fi…
Human Activity Recognition Process Using 3-D Posture Data
2015
In this paper, we present a method for recognizing human activities using information sensed by an RGB-D camera, namely the Microsoft Kinect. Our approach is based on the estimation of some relevant joints of the human body by means of the Kinect; three different machine learning techniques, i.e., K-means clustering, support vector machines, and hidden Markov models, are combined to detect the postures involved while performing an activity, to classify them, and to model each activity as a spatiotemporal evolution of known postures. Experiments were performed on Kinect Activity Recognition Dataset, a new dataset, and on CAD-60, a public dataset. Experimental results show that our solution o…
Super-resolution-based magnification of endothelium cells from biomicroscope videos of the cornea
2018
We present a practical, robust, and effective pipeline to compute a high-resolution (HR) image of the corneal endothelium starting from a low-resolution (LR) video sequence obtained with a general purpose slit lamp biomicroscope. An image quality typical of dedicated and more expensive confocal microscopes is achieved via software magnification by exploiting information redundancy in the video sequence. In particular, the HR image is generated from the best LR frames, obtained by identifying the most suitable endothelium video subsequence using a support vector machine-based learning approach, followed by a robust graph-based frame registration. Results on long, real sequences show that the…