This work describes a new segmentation method for robotic soccer applications. The approach called crossed-line segmentation is based on the combination of region classification and a border detector which meet homoge...
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ISBN:
(纸本)9783540688464
This work describes a new segmentation method for robotic soccer applications. The approach called crossed-line segmentation is based on the combination of region classification and a border detector which meet homogeneity criteria of medians. Experiments suggest that the method outperforms traditional procedure in terms of smoothing and segmentation accuracy. Furthermore, existing noise in the images is also observed to be reduced without missing the objects' borders.
Amateur boxing is one of the most exciting and interesting sports. Since referee of amateur boxing detects and counts number of punches that hit the opponents as scores for refereeing, an automatic glove tracking and ...
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ISBN:
(纸本)0780395387
Amateur boxing is one of the most exciting and interesting sports. Since referee of amateur boxing detects and counts number of punches that hit the opponents as scores for refereeing, an automatic glove tracking and punch detecting functions can help the judgment system because a machine has no bias. In this paper, we propose the method of glove tracking for amateur boxing refereeing. In this method, color-based segmentation is used to determine white region of glove in the first couple of frames and the glove in the next frames is tracked by opening window according to the movement vector of previous frames. To evaluate performance of proposed method, the experiments with videos of amateur boxer are performed. The results showed a glove can be tracked accurately.
Background: Machine learning (ML) prepares and trains a model through supervised or unsupervised learning methods. Sputum, a respiratory tract secretion, is a common laboratory specimen that aids in diagnosing respira...
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Different data acquisition methods are tailored at extracting particular characteristics from a scene and by combining their results a more robust scene description can be created. A method to fuse perceptual grouping...
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ISBN:
(纸本)0769507514
Different data acquisition methods are tailored at extracting particular characteristics from a scene and by combining their results a more robust scene description can be created. A method to fuse perceptual groupings extracted from color-based segmentation and depth information from stereo using supervised classification is presented. The merging of data from these two acquisition modules allows for a spatially coherent blend of smooth regions and detail in an image. Depth cues are used to limit the area of interest in the scene and to improve perceptual grouping solving subsegmentation and oversegmentation of the original images. The complexity of the algorithm does not exceed that of the individual acquisition modules. The resulting scene description can then be fed to an object recognition module for scene interpretation.
In this work, we present an efficient method for ego lane detection for micro-mobility systems as electric bicycles, scooters, or tricycles using RGB sequences from a driver's perspective. We combine a gradient-ba...
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In this work, we present an efficient method for ego lane detection for micro-mobility systems as electric bicycles, scooters, or tricycles using RGB sequences from a driver's perspective. We combine a gradient-based line detector with color-based segmentation to robustly find an approximation for the ego lane borders in various traffic environments. With given geometrical conditions of the scene and temporal inference, the approximation is improved, especially in difficult cases as when driving a curve. A key task thereby is the dynamic estimation of the vanishing point using optical flow vectors between two consecutive frames. Tests on over 2000 images taken with two different recording setups and different sampling rates show that the method reliably finds the borders of the ego lane in most of the samples and approximates the ego lane in a suitable way in curves. This is confirmed with a quantitative evaluation, determining an IoU of 75.28 %. A performance of 12 fps on a Raspberry Pi3 furthermore shows the suitability of our method for micromobility systems with low-cost and low-power hardware.
Lane detection plays a central role in intelligent transportation systems. While edge detection on intensity images has gained much popularity in the past, it usually results in noisy binary images. Most noticeably, t...
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ISBN:
(纸本)9781467347051
Lane detection plays a central role in intelligent transportation systems. While edge detection on intensity images has gained much popularity in the past, it usually results in noisy binary images. Most noticeably, the color information of the scene that may provide an important cue for lane detection has not been genuinely considered. In this paper, we propose a novel color-based lane detection system. Although color-based schemes have their fair share of issues, including varying illumination conditions, by relying on a lane mark color predictor obtained from an offline supervised training of Gaussian radial basis function (GRBF) networks, such issues can be appropriately overcome. Experimental results have demonstrated that the proposed approach, in contrast to predominantly edge-based approaches, can effectively eliminate erroneous edges that do not belong to the lane marks in well-structured scenes.
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