We present a geometric approach to multibody motion segmentation from line correspondences. Given three perspective views containing multiple moving objects, we demonstrate that after applying a polynomial embedding t...
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ISBN:
(纸本)0769525210
We present a geometric approach to multibody motion segmentation from line correspondences. Given three perspective views containing multiple moving objects, we demonstrate that after applying a polynomial embedding to the line correspondences, they became related by the so-called multibody trilinear constrain and its associated multibody trifocal tensor. We show how to obtain the individual trifocal tensor from the second order derivatives of the multibody trilinear constraint. Given trifocal tensors, we obtain the clustering of the motions and correspondences. Experimental results on synthetic and real dynamic scenes are presented
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 proposed a visual position calibration method using colored rectangle signboards for a mobile robot which is designed to work in a room environment. The rectangle signboards are placed in several kno...
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In this paper, we proposed a visual position calibration method using colored rectangle signboards for a mobile robot which is designed to work in a room environment. The rectangle signboards are placed in several known positions. By calculate the vanishing points in the image of the signboard, it is possible to obtain the relative direction and distance between the signboard and the robot by a single image. Experiments of position calibration were conducted. The results showed this method is effective and the errors between the set up positions and the experimental results were about 1.7 degrees and 3 cm when the distance to the signboards was set to 100 cm
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.
Feature subset selection is a fundamental problem of data mining. The mutual information of feature subset is a measure for feature subset containing class feature information. A hashing mechanism is proposed to calcu...
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Feature subset selection is a fundamental problem of data mining. The mutual information of feature subset is a measure for feature subset containing class feature information. A hashing mechanism is proposed to calculate the mutual information of feature subset. The feature relevancy is defined by mutual information. Redundancy-synergy coefficient, a novel redundancy and synergy measure for features to describe the class feature, is defined. In terms of information maximization rule, a bidirectional heuristic feature subset selection method based on mutual information and redundancy-synergy coefficient is presented. This study’s experiments show the good performance of the new method.
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 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
Feature subset selection is a fundamental problem of data mining. The mutual information of feature subset is a measure for feature subset containing class feature information. A hashing mechanism is proposed to calcu...
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Feature subset selection is a fundamental problem of data mining. The mutual information of feature subset is a measure for feature subset containing class feature information. A hashing mechanism is proposed to calculate the mutual information of feature subset. The feature relevancy is defined by mutual information. Redundancy-synergy coefficient, a novel redundancy and synergy measure for features to describe the class feature, is defined. In terms of information maximization rule, a bidirectional heuristic feature subset selection method based on mutual information and redundancy-synergy coefficient is presented. This study's experiments show the good performance of the new method.
In this paper, we proposed a robot self position identification method by active sound localization. This method can be used for autonomous security robots working in room environments. A system using a AIBO robot equ...
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In this paper, we proposed a robot self position identification method by active sound localization. This method can be used for autonomous security robots working in room environments. A system using a AIBO robot equipped with two microphones and wireless network is constructed and is used for position identification experiments. Arrival time differences to the microphones of robot are used as localization cues. To overcome the ambiguity of front-back confusion, a three-head position measurement method was proposed. The robot position can be identified by the intersection of circles restricted by the azimuth differences to different speaker pairs. By localizing three or four speakers as sound beacons positioned on known locations, the robot can identify its self position with an average error of about 7 cm in a 2.5 times 3.0 m 2 working space
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