Using real world images, two hierarchical graph-based segmentation methods are evaluated with respect to segmentations produced by humans. Global and local consistency measures do not show big differences between the ...
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Using real world images, two hierarchical graph-based segmentation methods are evaluated with respect to segmentations produced by humans. Global and local consistency measures do not show big differences between the two representative methods although human visual inspection of the results show advantages for one method. To a certain extent this subjective impression is captured by the new criteria of 'region size variation'
Most of the existing work regarding topology preserving hierarchies is mainly preoccupied with 2D domains. But recently attention has turned to 3D, and more generally, nD representations. Even more than in 2D, the nec...
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Most of the existing work regarding topology preserving hierarchies is mainly preoccupied with 2D domains. But recently attention has turned to 3D, and more generally, nD representations. Even more than in 2D, the necessity for reducing these representations exists and motivates the research in hierarchical structures i.e. pyramids. Using representations that support any dimension, like e.g. the combinatorial map, n dimensional irregular pyramids can be built, thus obtaining reduced representations of the original data, while preserving the topology. This paper presents 3D combinatorial maps and the primitive operations needed to simplify such representations. Minimal configurations of the three primitive topological configurations, simplex, hole, and tunnel, and two possible configurations for two tori are presented. Experimental results and possible applications show the potential of the approach
In this paper we discuss landmark based absolute localization of tiny autonomous mobile robots in a known environment. Landmark features are naturally occurring as it is not allowed to modify the environment with spec...
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Motivated by the requirements of modern archaeologists, we are developing a documentation system based on structured light for acquisition of ceramics. Fragments of ceramics are daily finds at excavations and importan...
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Motivated by the requirements of modern archaeologists, we are developing a documentation system based on structured light for acquisition of ceramics. Fragments of ceramics are daily finds at excavations and important for archaeological research, because their shape leads to information about ancient cultures. The shapes used for documentation are called profile lines and estimated by a vertical cross-section of orientated fragments. As ceramics have been produced using rotational plates for several thousands of years, the rotational axis can be used for orientation. Therefore we conducted experiments using existing methods for estimation of the rotational axis. The drawbacks of these methods are the requirement of either complete objects or industrialized quality of symmetry. Therefore we show a new method using circle templates, which has been inspired by the manual method of archaeologists. In this work we present results using previous and related work in comparison with the estimation of the rotational axis using circle templates. The results of the presented methods are shown for synthetic data, well-known fragments and real data acquired at an archaeological excavation. Finally a conclusion and an outlook is given.
In this study we analyze texture and profile features of painted strokes in order to identify the drawing media used for sketching underdrawings. Underdrawings are preliminary drawings on the panel prepared for painti...
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ISBN:
(纸本)0769525210
In this study we analyze texture and profile features of painted strokes in order to identify the drawing media used for sketching underdrawings. Underdrawings are preliminary drawings on the panel prepared for paintings and are unseen in the finished work. Cameras working in the near infrared range allow the visualization of underdrawings. Due to the tiny width of the strokes we perform an alignment of the feature extraction windows in order to obtain a major content of the stroke texture. The method is tested on strokes applied on test panels and underdrawing strokes in IR images of medieval paintings
In this paper, we apply a multiple regression method based on canonical correlation analysis (CCA) to face data modelling. CCA is a factor analysis method which exploits the correlation between two high dimensional si...
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In this paper, we apply a multiple regression method based on canonical correlation analysis (CCA) to face data modelling. CCA is a factor analysis method which exploits the correlation between two high dimensional signals. We first use CCA to perform 3D face reconstruction and in a separate application we predict near-infrared (NIR) face texture. In both cases, the input data are color (RGB) face images. Experiments show, that due to the correlation between input and output signal, only a small number of canonical factors are needed to describe the functional relation of RGB images to the respective output (NIR images and 3D depth maps) with reasonable accuracy
In this paper active feature models are proposed. They utilize local texture features and a statistical shape model for the reliable localization of landmarks in images. They are related to active appearance models, b...
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ISBN:
(纸本)0769525210
In this paper active feature models are proposed. They utilize local texture features and a statistical shape model for the reliable localization of landmarks in images. They are related to active appearance models, but instead of modelling the entire texture of an object they represent image texture by means of local descriptors. The approach has advantages with complex image data like anatomical structures that exhibit high texture variation with limited relevance for the recognition of the object location. Experimental results and the comparison to AAMs on different data sets indicate that active feature models can improve search speed and result accuracy, considerably
This paper presents a method for the fully automatic surveying of cutaneous hemangiomas by means of a hemangioma segmentation and a ruler visible in the images. The algorithm computes the spatial resolution of an imag...
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This paper presents a method for the fully automatic surveying of cutaneous hemangiomas by means of a hemangioma segmentation and a ruler visible in the images. The algorithm computes the spatial resolution of an image. Hemangioma segmentation is accomplished by a single-layer perceptron classification by means of pixel color features. The algorithm was evaluated on a set of 120 images. It achieves satisfactory results on images with clearly visible, saturated hemangiomas
Estimation of objects in a 3D space is a fundamental problem in computer vision and robotics. This paper describes an algorithm and its implementation for a vision module as a sensor of a biped robot (YABIRO). The emb...
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Estimation of objects in a 3D space is a fundamental problem in computer vision and robotics. This paper describes an algorithm and its implementation for a vision module as a sensor of a biped robot (YABIRO). The embedded vision sensor is able to estimate the position of objects like spheres in 3D space. Objects are defined with their size and color in a model. The vision sensor detects the positions or at least the directions to the objects and stores them in a history. The algorithm includes a new voting system for detected objects, based on how trustable the detection was, and a new edge filter to terminate edges on the circle border for the circle detection. The systems frame rate depends on the area of interest and lies between 5 Hz and 20 Hz. With a mechanical size of 36times32mm it is smaller than a matchbox
In this paper we discuss landmark based absolute localization of tiny autonomous mobile robots in a known environment. Landmark features are naturally occurring as it is not allowed to modify the environment with spec...
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In this paper we discuss landmark based absolute localization of tiny autonomous mobile robots in a known environment. Landmark features are naturally occurring as it is not allowed to modify the environment with special navigational aids. These features are sparse in our application domain and are frequently occluded by other robots. This makes simultaneous acquisition of two or more landmarks difficult. Therefore, we propose a system that requires a single landmark feature. The algorithm is based on range measurement of a single landmark from two arbitrary points whose displacement can be measured using dead-reckoning sensors. Range estimation is done with a stereo vision system. Simulation results show that the robot can localize itself if it can estimates range of the same landmark from two different position and if the displacement between the two position is known.
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