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Very high resolution radar satellites such as TerraSAR-X open new possibilities for image registration due to their very accurate absolute geo-location. Thus optical and SAR imagery registration seems to be an attractive solution for accurate and automatic common tie points extraction. We propose to use template based image matching approach because it allows defining features/templates using a priori...
Deep learning algorithms such as convolutional neural networks (CNN) have been successfully applied in computer vision. This paper attempts to adapt the optical camera-oriented CNN to its microwave counterpart, i.e. synthetic aperture radar (SAR). As a preliminary study, a single layer of convolutional neural network is used to automatically learn features from SAR images. Instead of using the classical...
This study presents single-trial classification performance on high density Near Infrared Spectroscopy (NIRS) data collected from the prefrontal cortex of 11 healthy subjects while performing working memory tasks and idle condition. The NIRS data collected comprised a total of 40 trials of n-back tasks for 2 difficulty levels: n=1 for easy and n=3 for hard. The single-trial classification was performed...
Moving vehicle detection in dynamical scene is a significant but challenging problem in these days. A new and effective approach to extract moving vehicles is proposed in this paper. In our method, Harris corner and Lucas-Kanade (L-K) optical flow was adopted to generalize feature-point optical flow field between two consecutive frames which obtained from monocular moving camera, and then vector quantization...
Automatic fusion of aerial optical imagery and untextured LiDAR data has been of significant interest for generating photo-realistic 3D urban models in recent years. However, unsupervised, robust registration still remains a challenge. This paper presents a new registration method that does not require priori knowledge such as GPS/INS information. The proposed algorithm is based on feature correspondence...
In this paper, we present a multi-scale approach based on superpixel classification for optic cup localization. Our approach provides 3 major contributions. First, a contrast enhancement scheme is proposed to reduce illumination influence and enhance feature discrimination. Second, features are extracted from multiple superpixels scales for richer description of the optic cup. Third, a unique cup...
This paper proposes a high accuracy and fast image restoration approach to restore a sequence of atmospheric turbulence degraded frames of a remote object or scene. A coarse-to-fine optical flow technique is employed to estimate the dense motion fields of the frames against a reference frame. The First Register Then Average And Subtract (FRTAAS) method is used to correct the geometric distortions...
Glaucoma is the second leading cause of blindness worldwide. It is a disease in which fluid pressure in the eye increases continuously, damaging the optic nerve and causing vision loss. Computational decision support systems for the early detection of glaucoma can help prevent this complication. The retinal optic nerve fibre layer can be assessed using optical coherence tomography, scanning laser...
This paper presents a novel pedestrian detection framework for efficient detection of both unoccluded and occluded pedestrians, thereby proposing an efficient technique for pedestrian detection in real-time environment. Our framework consists of two layers of detection, the first layer using full body detectors for accurate detection of unoccluded pedestrians and then a cascaded layer of part based...
In this paper, we present an unsupervised framework using domain priors extracted from the primary structures of the optic nerve head for automated optic cup localization. Our approach provides 3 major contributions. First, we identify a new domain prior, optic cup origin. This prior is derived from the physiological understanding that the central retinal vessels traces its origin from the optic cup...
This paper presents a method for blood vessel segmentation in retinal images based on the nonsubsampled contourlet transform (NSCT). The method uses a line detector and different directions of the NSCT subbands to detect the direction of blood vessel for each NSCT level. Then, the method computes three kinds of features using the orthogonal direction of blood vessel of the NSCT coefficients. After...
Near-infrared spectroscopy (NIRS)-based Brain-Computer Interface (BCI) was recently proposed to assess level of numerical cognition in subjects. However, existing feature extraction method was only proposed for low density 16 channels NIRS-based BCI. This study investigates the performance of a high density 348 channels NIRS-based BCI on 8 healthy subjects while they solve mental arithmetic problems...
This paper presents a novel personal identification method by extracting unique object features from optical speckle patterns using the SIFT (Scale Invariant Feature Transform) algorithm. Accurate identification is achieved by developing an invariant speckle capturing device and recognition criteria. Experimental results show that optical speckle pattern of a given material is invariant after slight...
Localization of the macula centre is an important step in retinal image analysis, in particular for macular disease. We propose the use of a superpixel-based approach for macular localization. Features are extracted from the superpixels, including a proposed feature which aims to describe the extent of the local region due to the superpixel influence. These features are used to calculate probability...
In this paper we examine the causes of one of the major shortcomings of current natural feature registration approaches, failure to register when the camera's view approaches parallel to the marker. The methods used by current registration algorithms in the attempt to overcome this problem are reviewed, and a novel tracking based approach called the Optical-flow Perspective Invariant Registration...
This paper presents a method for ship detection using texture statistics from optical satellite images. The proposed method focuses on the extraction of ship candidates. First, a structural texture descriptor derived from local multiple patterns is introduced to describe image texture features, and then two statistical histograms are generated by quantizing texture features to describe the texture...
An optical flow odometry method for mobile robots using a single downward-looking camera is presented. The method is robust to the robot's own moving shadow and other sources of error. Robustness derives from two techniques: prevention of feature selection on or near shadow edges and elimination of outliers based on inconsistent motion. In tests where the robot's shadow dominated the image, prevention...
Identification of motion patterns in video is an important problem because it is the first step towards analysis of complex multi-person behaviors to obtain long-term interaction models. In this paper, we will present a flow based technique to identify spatio-temporal motion patterns in a multi-object video. We use the Helmholtz decomposition of optical flow and compute singular points corresponding...
Capsule endoscopy (CE) is a revolutionary technology that enables physicians to examine the whole digestive tract in human body in a minimally noninvasive manner. However, it is reported that the large amount of video data yielded in each examination produces a troublesome and time consuming task for a clinician and it takes about two hours on average to examine. To reduce such a heavy load for clinicians,...
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