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Stereo vision systems in a Robotic navigation environment determine the depth in the form of a depth map image from two or more images which are taken at the same time, but from slightly different viewpoints. Ground suppression from depth map is essential for object reconstruction in 3D environment as the ground surface is considered as traveling medium than as an object. Ground separated depth map...
Present object detection methods working on 3D range data are so far either optimized for unstructured offroad environments or flat urban environments. We present a fast algorithm able to deal with tremendous amounts of 3D lidar measurements. It uses a graph-based approach to segment ground and objects from 3D lidar scans using a novel unified, generic criterion based on local convexity measures....
Computing world distances of scene features from the captured images is a common task in image analysis and scene understanding. Projective geometry based methods focus on measuring distance from one single image, the scope of measurable scene is limited by the field-of-view (FOV) of one single camera. With a full view panorama, the scope of measurable scene is no longer limited by FOV. However, the...
This work introduces a novel streamline seeding technique based on dual streamlines that are orthogonal to the vector field, instead of tangential. The greedy algorithm presented here produces a net of orthogonal streamlines that is iteratively refined resulting in good domain coverage and a high degree of continuity and uniformity. The algorithm is easy to implement and efficient, and it naturally...
Body language is a connection way between humans. Computer vision based system try to facilitate human connections using human gesture interpretations. This paper proposes a method based on hand gesture recognition for device control using inner distance feature. Our method consists of three primary parts. 1) Hand segmentation and state identification. 2) Hand tracking, and 3) gesture recognition...
In advanced driving assistance systems, it is important to be able to detect the region covered by the road in the images. This paper proposes a method for estimating the road region in images captured by a vehicle-mounted monocular camera. Our proposed method first estimates all of relevant parameters for the camera motion and the 3D road plane from correspondence points between successive images...
The importance of accurate early diagnostics of dyslexia that severely affects the learning abilities of children cannot be overstated. Neuropathological studies have revealed an abnormal anatomy of the cerebral white matter (CWM) in dyslexic brains. We explore a possibility of distinguishing between dyslexic and normal (control) brains by a quantitative shape analysis of CWM gyrifications on 3D Magnetic...
Symmetry is an important property of objects and is exhibited in different forms e.g., bilateral, rotational, etc. This paper presents an algorithm for computing the bilateral symmetry of silhouettes of shallow objects under perspective distortion, exploiting the invariance of the cross ratio to projective transformations. The basic idea is to use the cross ratio to compute a number of midpoints of...
Digital processing of medical images has helped physicians and patients during past years by allowing examination and diagnosis on a very precise level. Nowadays possibly the biggest deal of support it can offer for modern healthcare is the use of high performance computing architectures to treat the huge amounts of data that can be collected by modern acquisition devices. This paper presents a parallel...
The importance of accurate early diagnosis of dyslexia, which severely affects the learning abilities of children, cannot be overstated. Neuropathological studies have revealed an abnormal anatomy of the cerebral white matter (CWM) in dyslexic brains. We explore a possibility of distinguishing between dyslexic and normal (control) brains by a quantitative shape analysis of CWM gyrifications on 3D...
In many neurophysiological studies, understanding the neuronal circuitry of the brain requires detailed 3D models of the nerve cells and their synapses. Typically, researchers build the 3D models by manually tracing the 2D cross-sectional profiles of the 3D structures from serial electron micrograph (EM) stacks and then construct the models from these 2D contours. While current computer-aided techniques...
This paper presents a segmentation and recognition method of 3D objects in automatic navigation. In the first part of this paper, a segmentation method based on nautical scene is proposed, which is composed of image preprocess, ROI detection, subarea process and object detection. In addition, an applied visual resolution calculation method is presented to control the simplification of original 3D...
This paper presents a novel approach for marker-less 3D full body pose tracking using adaptive particle filter. Firstly, the search space decomposition strategy and body part segmentation method are used to reduce the calculation complexity due to the large degrees of freedom. Then an adaptive particle filter is adopted to track each body part. This new technique is a significant improvement over...
The iris is a highly accurate biometric identifier. However widespread adoption is hindered by the difficulty of capturing high-quality iris images with minimal user co-operation. This paper describes a first-generation prototype iris identification system designed for stand-off cooperative access control. This system identifies individuals who stand in front of and face the system after 3.2 seconds...
The use of gradients in text images is nowadays quite frequent. Existing segmentation methods encounter serious problems when it comes to modern text images where gradients might appear in the background or the foreground or both at the same time. This paper presents an approach for lightness gradient areas detection based on the Hough Transform. The issues arising are discussed, and results are presented...
Contactless human-machine-interfaces (HMIs) are an important issue in various applications where a haptic interaction with an input device is not possible or not appropriate. Newly developed Time-of-Flight cameras provide 3D information of the observed scene in real-time at constant lateral resolutions of thousands of pixels. Additionally, a gray-value image of the observed scene is available. Our...
In this paper we introduce a large body of virtual human action silhouette (ViHASi) data that we have recently generated for the purpose of evaluating a family of action recognition methods. These are the silhouette-based human action recognition methods. This synthetic multi-camera video data-set consists of 20 action classes, 9 actors and up to 40 synchronized perspective cameras. This data-set...
A new vision and inertial pose estimation system was implemented for real-time handheld augmented reality (AR). A sparse set of 3D cone fiducials are utilized for scalable indoor/outdoor tracking, as opposed to traditional planar patterns. The cones are easy to segment and have a large working volume which makes them more suitable for many applications. The pose estimation system receives measurements...
This paper presents a method for recognizing human actions in a multi-camera setup. The proposed method automatically extracts significant points on the human body, without the need of artificial markers. A sophisticated appearance-based tracking able to cope with occlusions is exploited to extract a probability map for each moving object. A segmentation technique based on mixture of Gaussians is...
This paper presents a vision based method for grasp classification. It is developed as part of a Programming by Demonstration (PbD) system for which recognition of objects and pick-and-place actions represent basic building blocks for task learning. In contrary to earlier approaches, no articulated 3D reconstruction of the hand over time is taking place. The indata consists of a single image of the...
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