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In most big cities, firearm assault is a common crime. Some state of the art research aim to recognize firearms once they were fired. However, to prevent this type of criminal behavior it is necessary to detect firearms in real time, before they are fired, and maintaining at minimum false alarms. In this paper, we propose a method to detect hand guns by using its shape and real dimensions. The proposed...
Tuberculosis (TB) is an infectious disease caused by the bacteria Mycobacterium tuberculosis or simply M. tuberculosis. It is primarily an infection of lungs, but it can also affect other parts of the body such as brain, intestine, kidney and spine. TB remains one of the leading cause of death in developing countries, although most are preventable if diagnosed early and treated. Among the available...
In topology representations such as maps, carbon nanotubes, and cellular networks, neighboring cells are assigned different exclusive colors to represent different characteristics. In the previous research, based on the fourcolor theorem, an algorithm that can allocate exclusive channels among neighbors using only four channels in a polygonal cluster sensor network is proposed. The performance of...
We propose a real-time algorithm for the generic classification of humans and objects in 3D scenes. The algorithm does not depend on color information and works with depth data alone, making it very flexible for a wide area of applications. Further, we will show that it is very resistant to occlusion and will give correct classification results even in cases, where only a fraction of a full human...
While hand geometry trait has been widely used to perform biometric recognition, majority of the methods employ images acquired against a uniform background. If segmentation of the hand is implemented, existing techniques can be used in cluttered backgrounds as well. This paper presents an approach for accurate segmentation of human hands for images following the aforementioned conditions using skin...
In this work, we explore the problem of generating fantastic special-effects for the typography. It is quite challenging due to the model diversities to illustrate varied text effects for different characters. To address this issue, our key idea is to exploit the analytics on the high regularity of the spatial distribution for text effects to guide the synthesis process. Specifically, we characterize...
Finding what is and what is not a salient object can be helpful in developing better features and models in salient object detection (SOD). In this paper, we investigate the images that are selected and discarded in constructing a new SOD dataset and find that many similar candidates, complex shape and low objectness are three main attributes of many non-salient objects. Moreover, objects may have...
Neural Style Transfer has shown very exciting results enabling new forms of image manipulation. Here we extend the existing method to introduce control over spatial location, colour information and across spatial scale. We demonstrate how this enhances the method by allowing high-resolution controlled stylisation and helps to alleviate common failure cases such as applying ground textures to sky regions...
For machines to interact with the physical world, they must understand the physical properties of objects and materials they encounter. We use fabrics as an example of a deformable material with a rich set of mechanical properties. A thin flexible fabric, when draped, tends to look different from a heavy stiff fabric. It also feels different when touched. Using a collection of 118 fabric samples,...
While the ready availability of 3D scan data has influenced research throughout computer vision, less attention has focused on 4D data, that is 3D scans of moving non-rigid objects, captured over time. To be useful for vision research, such 4D scans need to be registered, or aligned, to a common topology. Consequently, extending mesh registration methods to 4D is important. Unfortunately, no ground-truth...
Rotoscoping, the detailed delineation of scene elements through a video shot, is a painstaking task of tremendous importance in professional post-production pipelines. While pixel-wise segmentation techniques can help for this task, professional rotoscoping tools rely on parametric curves that offer the artists a much better interactive control on the definition, editing and manipulation of the segments...
When building artificial intelligence systems that can reason and answer questions about visual data, we need diagnostic tests to analyze our progress and discover short-comings. Existing benchmarks for visual question answering can help, but have strong biases that models can exploit to correctly answer questions without reasoning. They also conflate multiple sources of error, making it hard to pinpoint...
Understanding shading effects in images is critical for a variety of vision and graphics problems, including intrinsic image decomposition, shadow removal, image relighting, and inverse rendering. As is the case with other vision tasks, machine learning is a promising approach to understanding shading - but there is little ground truth shading data available for real-world images. We introduce Shading...
We study the notion of consistency between a 3D shape and a 2D observation and propose a differentiable formulation which allows computing gradients of the 3D shape given an observation from an arbitrary view. We do so by reformulating view consistency using a differentiable ray consistency (DRC) term. We show that this formulation can be incorporated in a learning framework to leverage different...
The main aim of this paper is to reduce the computational time, to increase the complexity ratio and to improve the image quality by applying dither Dither Block Truncation coding algorithm with different similarity comparison algorithm, as different approaches are followed to improve the quality of an image, ODBTC is one of the approach, but to improve the quality we will also include some of the...
Vehicle detection and classification is an essential application in traffic surveillance system (TSS). However, recognizing moving vehicle at nighttime is more challenging because of either poorly (lack of street lights) or brightly illuminations and chaos traffic of motorbikes. Adding to this is various type of vehicles travels on the same road which falsifies the pairing results. So, this research...
Accurate cell detection is often an essential prerequisite for subsequent cellular analysis in computer aided diagnosis (CAD) for histopathlogy images. It is challenging due to high cell density, touching cells, low contrast, variant cell shapes and sizes, weak boundaries and the use of different image acquisition techniques. Existing methods are often struggling at tackling with the challenges at...
Measuring area of tumor in human's brain from only single image may provide incorrect information for further diagnosis. Generally, a doctor or an expert must examine a brain tumor from several sequential MRI images to conclude its size or the severity level of patient's illness. To imitate the way a doctor diagnosing such case in a real situation, some digital image processing techniques are proposed...
Traffic light detection (TLD) is a vital part of both intelligent vehicles and driving assistance systems (DAS). General for most TLDs is that they are evaluated on small and private datasets making it hard to determine the exact performance of a given method. In this paper we apply the state-of-the-art, real-time object detection system You Only Look Once, (YOLO) on the public LISA Traffic Light...
This paper describes the outcomes of relevant feature extraction and identification methods to aid successfully aircraft door detection. The system has to work day and night, rain or shine under all-weather conditions. The proposed solution consists of a suite of relevant extracted and identified features that characterize aircraft door (e.g. door windows, handle, text, footplate, arrow, frame lines)...
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