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We propose a method to derive shading by referring to an unspecified object to synthesize CG objects realistically into an actual scene. Since our method does not require specific light probes and can be implemented with a commercial RGB + depth sensor, it is applicable to consumer environments. The method conducts spherical harmonic (SH) basis functions regression against luminance of the reference...
We propose a fast and efficient method for localization and rectification of a dominant rectangular region within an image, particularly suitable for mobile Augmented Reality applications. This approach can deal with perspective distortion and high-frequency structures such as text. The resulting image may be used for planar tracking or as input for subsequent image processing tasks. We demonstrate...
The paper proposes a novel endoscope motion estimation method that bases an aggressive particle filter (APF) for enhancing electromagnetic tracking (EMT) during guided endoscopy. We explore an APF strategy to resolve two main limitations of EMT sensor measurements: (1) inaccuracy due to airway deformation and (2) instability or jitter errors because of magnetic field distortion. During such a strategy,...
We present a novel motion descriptor for gesture recognition based on depth camera. Since each object motion leads to a specific depth change characterized by depth difference, we can recognize object motion via Depth Difference Distribution (DDD) in object region. The DDD is approximated by DDD descriptor in three steps. First, each pixel's depth difference value is quantified into Depth Difference...
Indirect ImmunoFluorescence (IIF) is currently the recommended method for the detection of antinuclear autoantibodies(ANA). It is an effective technique to reveal the presence of auto immune diseases; however, it is a subjective method and hence dependent on the experience and expertise of the physician. Moreover, inter-observer variability limits the reproducibility of IIF reading. To this end, we...
Eye detector and eye tracker have been individually used to solve the task of eye localization in video. Although the eye detection based approach seems to be robust especially in frontal view faces and opened eyes, its performance drops dramatically in the presence of large head pose change and closed eyes. Meanwhile, eye tracking based approaches can estimate closed eyes and eyes in extreme head...
This paper explores the challenge of optimally categorizing regions for man-made environment. We propose using the histogram of oriented gradients (HOG) features for characterizing image regions, and propose an algorithm based on the entropy of HOG to select relevant regions. We also propose a regionsensitive feature selection algorithm for image registration. The algorithms are applied to several...
We present an approach for detecting moving objects from a dynamic video sequence, using a stereo camera system. The detection of moving objects is a challenging problem, especially when backgrounds are also time-varying due to the concurrent changes of moving objects and backgrounds. Most of the previous approaches have been limited to the use of appearance information such as colors and 2D motions...
In this paper, we present a new method for text extraction in real scene images. We propose first a skeleton based descriptor to describe the strokes of the text candidates that compose a spatial relation graph. We then apply the graph cuts algorithm to label the nodes of the graph as text or non-text. We finally refine the resulted text lines candidates by classifying them using a kernel SVM. To...
In this article, we present a novel set of features for detection of text in images of natural scenes using a multi-layer perceptron (MLP) classifier. An estimate of the uniformity in stroke thickness is one of our features and we obtain the same using only a subset of the distance transform values of the concerned region. Estimation of the uniformity in stroke thickness on the basis of sparse sampling...
In this paper we present a novel method for automatic text-line parameter selection for stereo image pairs. The parameters are selected such that correspondence between the same content in a stereo pair is maximized. Automatic parameter selection has been carried out by establishing robust text-line correspondence which is also a contribution of the presented work. The proposed method is applied to...
Large-scale digitisation of historical documents demands robust methods that cope with the presence of frequent distortions and noisy artefacts. This paper presents a hybrid text line segmentation method that uses a novel data structure and a rule base to combine the strengths of top-down and bottom-up approaches while minimising their weaknesses. The effectiveness of the proposed approach has been...
In this paper, we propose a novel binary-based cost computation and aggregation approach for stereo matching problem. The cost volume is constructed through bitwise operations on a series of binary strings. Then this approach is combined with traditional winner-take-all strategy, resulting in a new local stereo matching algorithm called binary stereo matching (BSM). Since core algorithm of BSM is...
Stereo matching is a challenging problem, especially in the presence of noise or of weakly textured objects. Using temporal information in a binocular video sequence to increase the discriminability for matching has been introduced in the recent past, but all the proposed methods assume either constant disparity over time, or small object motions, which is not always true. We introduce a novel stereo...
In this paper, we propose a simple method for the ghost detection problem in the context of merging multiple low dynamic range (LDR) images to form a high dynamic range (HDR) image. We show that the second biggest singular values extracted over local spatiotemporal neighbourhoods can be effectively used for ghost region detection. Furthermore, we combine the proposed method with an exposure fusion...
While the performance of Robust Principal Component Analysis (RPCA), in terms of the recovered low-rank matrices, is quite satisfactory to many applications, the time efficiency is not, especially for scalable data. We propose to solve this problem using a novel fast incremental RPCA (FRPCA) approach. The low rank matrices of the incrementally-observed data are estimated using a convex optimization...
In this work, we investigate the applicability of the Kinect depth camera as a robot mounted measurement unit. In contrast to traditional head mounted robot sensors, Kinect is small, cheap and delivers robust depth measurements on a variety of scenes. In the course of applying it on a robot arm, we solve a number of problems: we reduce the sensor working distance to a few centimeters, replace the...
Most of the state-of-the-art algorithms of restoring single blurred image are sensitive to image noise and artifacts. Our idea is to learn an adaptive filter for blind deconvolution to remedy this problem. We use this auxiliary filter to progressively suppress image noise in early stage of kernel estimation, leading to a robust kernel estimation algorithm. Our approach can naturally handle image noise...
Many enterprises strive toward the integration of input communication channels into their internal business processes. To help them, we propose to drive input channel document analysis (DA) by formalizing information expectations from current process instances in Attentive Task (AT) templates. This requires, however, to map incoming request documents to the related AT from a set of ATs. For this purpose,...
To enhance ICP monitoring of Traumatic Brain Injury (TBI) patients, much research effort has been attracted to the development auto-alarming systems and forecasting methods to predict impending intracranial hypertension episodes. Nevertheless, the performance of the proposed methods are often limited by the presence of artifacts in the ICP signal. To address this bottleneck, we propose novel artifact...
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