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.
Video scene detection, the task of temporally dividing a video into its semantic sections, is an important process for effective analysis of heterogeneous video content. With the increased amount of video available for consumption, video scene detection becomes more and more important by providing means for effective video summarization, search and retrieval, browsing, and video understanding. We...
In trying to understand the big picture of how users learn to program in App Inventor, we want to be able to represent projects in a way suitable for large scale learning analytics. Here I present different representations of projects that could potentially be used to identify App Inventor projects that have structural similarities to each other, e.g., projects created by users following tutorials...
Research into computational jigsaw puzzle solving, an emerging theoretical problem with numerous applications, has focused in recent years on puzzles that constitute square pieces only. In this paper we wish to extend the scientific scope of appearance-based puzzle solving and consider ’’brick wall” jigsaw puzzles – rectangular pieces who may have different sizes, and could be placed next to each...
Person Re-Identification (person re-id) is a crucial task as its applications in visual surveillance and human-computer interaction. In this work, we present a novel joint Spatial and Temporal Attention Pooling Network (ASTPN) for video-based person re-identification, which enables the feature extractor to be aware of the current input video sequences, in a way that interdependency from the matching...
As an emissive display, the organic light emitting diode (OLED) endure an indispensable role on the market growth of consumer electronics. Despite the preferable power efficiency, the active matrix OLED (AMOLED) displays still consume large energy. To adaptively increase the power efficiency of AMOLED displays, we propose an adjustable pixel dimming algorithm based on the structural similarity metric...
Together with the technology advancement, Computer Vision plays an important role in enhancing smart computing systems to help people overcome obstacles in their daily lives. One of the common troublesome problems is human memorization ability, especially memorizing things such as personal items. It is annoying for people to waste their time finding lost items manually by recall or notes. This motivates...
We present a novel method for removing rain streaks from a single input image by decomposing it into a rain-free background layer B and a rain-streak layer R. A joint optimization process is used that alternates between removing rain-streak details from B and removing non-streak details from R. The process is assisted by three novel image priors. Observing that rain streaks typically span a narrow...
Despite the substantial progress in recent years, the image captioning techniques are still far from being perfect. Sentences produced by existing methods, e.g. those based on RNNs, are often overly rigid and lacking in variability. This issue is related to a learning principle widely used in practice, that is, to maximize the likelihood of training samples. This principle encourages high resemblance...
Many existing person re-identification (PRID) methods typically attempt to train a faithful global metric offline to cover the enormous visual appearance variations, so as to directly use it online on various probes for identity match- ing. However, their need for a huge set of positive training pairs is very demanding in practice. In contrast to these methods, this paper advocates a different paradigm:...
Because data collection in HPC systems happens on the nodes and is easily related to the job running on the node, tools presenting the data and subsequent analyses to the user generally present them at the job level. Our position is that this is the wrong level of abstraction and thus limits the value of the analyses, often dissuading users from using any of the offered tools. In this paper we present...
Microbubble based contrast-enhanced ultrasound (CEUS) enables the visualization of vascularity given the tendency of microbubbles to function as a blood pooling agent. Using contrast specific ultrasound (US) imaging, it is possible to quantify the kinetics of these agents and derive various perfusion metrics. In this ongoing clinical study, we evaluate the feasibility of using these microbubble based...
The major design challenges of ASIC design, like power dissipation, timing, voltage-drop, interconnect and reliability are tackled during the Physical Design phase of any flow. The placement procedure can significantly modify parts of the design and consequently metrics relevant to the aforementioned challenges. Text reports cannot always generate useful insight based solely on these metrics. Design...
Software visualizations provide many different complex views with different filters and metrics. But often users have a specific question to which they want to have an answer or they need to find the best visualization by themselves and are not aware of other metrics and possibilities of the visualization tool. We propose an interaction with software visualizations based on a conversational interface...
In Gradient-Based Cross-Spectral Stereo Matching (GB-CSSM) output disparity maps tend to produce coarse results that are, for the most part, reliable. However, general methods of improving the performance of disparity maps generated from the Cross-Spectral comparison of visual and full infrared input images are non-existent. In particular, previous works fail to address the role and interaction of...
Clustering techniques have gained great popularity in neuroscience data analysis especially in analysing data from complex experiment paradigm where it is hard to apply traditional model-based method. However, when employing clustering analysis, many clustering algorithms are available nowadays and even with an individual clustering algorithm, choices like parameter settings and distance metrics are...
Mass casualty events caused by a biological weapon require fully capable first response teams. However, human first responders are equipped with protective gear, which limits their capabilities to complete tasks. Robots can be employed to work collaboratively with the first responders in order to augment the human's reduced abilities. The robot needs to understand and adapt to the human's workload...
Image quality assessment (IQA) plays a crucial role in monitoring quality control in image communication systems, and in benchmarking and optimizing parameters in enhancement algorithms. The full-reference IQA metrics require a good-quality reference image, obtaining which may not be practical in real-life applications. This paper, therefore, proposes a no-reference IQA metric based on the hypothesis...
Rapid growing of multimedia processing technologies enables many creative and powerful new applications. Due to the availability of multimedia reconstruction and editing tools, multimedia authentication gained a considerable attention. Some authentication is to be performed during the transmission of data via insecure networks. Data encryption is one of the frequently used method for secure data transmission...
Event detection in unconstrained videos is conceived as a content-based video retrieval with two modalities: textual and visual. Given a text describing a novel event, the goal is to rank related videos accordingly. This task is zero-exemplar, no video examples are given to the novel event. Related works train a bank of concept detectors on external data sources. These detectors predict confidence...
Image captioning is a challenging problem owing to the complexity in understanding the image content and diverse ways of describing it in natural language. Recent advances in deep neural networks have substantially improved the performance of this task. Most state-of-the-art approaches follow an encoder-decoder framework, which generates captions using a sequential recurrent prediction model. However,...
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.