摘要 :
The sufficient condition that guarantees perfect segmentation for an image with PCNNs when the intensity ranges of adjacent regions overlap is one of the main results presented in reference[1]. However, with deep understanding of ...
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The sufficient condition that guarantees perfect segmentation for an image with PCNNs when the intensity ranges of adjacent regions overlap is one of the main results presented in reference[1]. However, with deep understanding of the derivation process used in [1], it is shown in this paper that it is not a sufficient condition. The conditions for perfect image segmentation when there is an overlap in intensity ranges of adjacent regions are still remained unsolved.
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摘要 :
The sufficient condition that guarantees perfect segmentation for an image with PCNNs when the intensity ranges of adjacent regions overlap is one of the main results presented in reference[1]. However, with deep understanding of ...
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The sufficient condition that guarantees perfect segmentation for an image with PCNNs when the intensity ranges of adjacent regions overlap is one of the main results presented in reference[1]. However, with deep understanding of the derivation process used in [1]. it is shown in this paper that it is not a sufficient condition. The conditions for perfect image segmentation when there is an overlap in intensity ranges of adjacent regions are still remained unsolved.
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摘要 :
Behavioral and neurophysiological findings in vision suggest that grouping by proximity occurs earlier than grouping by similarity. The present study investigated in the haptic modality whether proximity is an earlier/faster group...
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Behavioral and neurophysiological findings in vision suggest that grouping by proximity occurs earlier than grouping by similarity. The present study investigated in the haptic modality whether proximity is an earlier/faster grouping principle than texture similarity. In this study, we compared responses to stimuli grouped by proximity with that grouped by similarity (surface texture) using a speeded orientation detection task performed on a novel haptic device. The apparatus was interfaced with a computer to allow controlled stimulus presentation and accurate registration of the responses. Two were the main results of the experiment: (1) response times for stimulus patterns grouped by proximity were faster compared to those patterns grouped by similarity; and (2) in those patterns grouped by proximity, vertical symmetric patterns were classified faster than horizontal symmetric patterns. We conclude that the Gestalt principles of proximity and similarity apply to the haptic modality. As in vision, grouping by proximity is faster than grouping by similarity, especially when symmetric grouped patterns are oriented vertically in line with the body midline axis.
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摘要 :
Understanding and exploiting the abilities of the human visual system is an important part of the design of usable user interfaces and information visualizations. Good design enables quick, easy and veridical perception of key com...
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Understanding and exploiting the abilities of the human visual system is an important part of the design of usable user interfaces and information visualizations. Good design enables quick, easy and veridical perception of key components of that design. An important facet of human vision is its ability to seemingly effortlessly perform "perceptual organization; it transforms individual feature estimates into perception of coherent regions, structures, and objects. We perceive regions grouped by proximity and feature similarity, grouping of curves by good continuation, and grouping of regions of coherent texture. In this paper, we discuss a simple model for a broad range of perceptual grouping phenomena. It takes as input an arbitrary image, and returns a structure describing the predicted visual organization of the image. We demonstrate that this model can capture aspects of traditional design rules, and predicts visual percepts in classic perceptual grouping displays.
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The identification and processing of similarities in the data play a key role in multiple application scenarios. Several types of similarity-aware operations have been studied in the literature. However, in most of the previous wo...
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The identification and processing of similarities in the data play a key role in multiple application scenarios. Several types of similarity-aware operations have been studied in the literature. However, in most of the previous work, similarity-aware operations are studied in isolation from other regular or similarity-aware operations. Furthermore, most of the previous research in the area considers a standalone implementation, i.e., without any integration with a database system. In this demonstration we present SimDB, a similarity-aware database management system. SimDB supports multiple similarity-aware operations as first-class database operators. We describe the architectural changes to implement the similarity-aware operators. In particular, we present the way conventional operators' implementation machinery is extended to support similarity-ware operators. We also show how these operators interact with other similarity-aware and regular operators. In particular, we show the effectiveness of multiple equivalence rules that can be used to extend cost-based query optimization to the case of similarity-ware operations.
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摘要 :
The identification and processing of similarities in the data play a key role in multiple application scenarios. Several types of similarity-aware operations have been studied in the literature. However, in most of the previous wo...
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The identification and processing of similarities in the data play a key role in multiple application scenarios. Several types of similarity-aware operations have been studied in the literature. However, in most of the previous work, similarity-aware operations are studied in isolation from other regular or similarity-aware operations. Furthermore, most of the previous research in the area considers a standalone implementation, i.e., without any integration with a database system. In this demonstration we present SimDB, a similarity-aware database management system. SimDB supports multiple similarity-aware operations as first-class database operators. We describe the architectural changes to implement the similarity-aware operators. In particular, we present the way conventional operators' implementation machinery is extended to support similarity-ware operators. We also show how these operators interact with other similarity-aware and regular operators. In particular, we show the effectiveness of multiple equivalence rules that can be used to extend cost-based query optimization to the case of similarity-ware operations.
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摘要 :
Understanding and exploiting the abilities of the human visual system is an important part of the design of usable user interfaces and information visualizations. Good design enables quick, easy and veridical perception of key com...
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Understanding and exploiting the abilities of the human visual system is an important part of the design of usable user interfaces and information visualizations. Good design enables quick, easy and veridical perception of key components of that design. An important facet of human vision is its ability to seemingly effortlessly perform "perceptual organization"; it transforms individual feature estimates into perception of coherent regions, structures, and objects. We perceive regions grouped by proximity and feature similarity, grouping of curves by good continuation, and grouping of regions of coherent texture. In this paper, we discuss a simple model for a broad range of perceptual grouping phenomena. It takes as input an arbitrary image, and returns a structure describing the predicted visual organization of the image. We demonstrate that this model can capture aspects of traditional design rules, and predicts visual percepts in classic perceptual grouping displays.
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We present a new technique to produce composite images called Puzzle Image Mosaic (PIM). The method is inspired by Jigsaw Image Mosaic (JIM), where image tiles of arbitrary shape are used to compose the final picture. The JIM appr...
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We present a new technique to produce composite images called Puzzle Image Mosaic (PIM). The method is inspired by Jigsaw Image Mosaic (JIM), where image tiles of arbitrary shape are used to compose the final picture. The JIM approach leads to impressive results, but the required computation time is high. We propose an algorithm that produces good results in lower time. The technique takes advantage from recent results about data structures aimed to optimize proximity queries. Experimental results prove the soundness of our method.
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摘要 :
We present a new technique to produce composite images called Puzzle Image Mosaic (PIM). The method is inspired by Jigsaw Image Mosaic (JIM), where image tiles of arbitrary shape are used to compose the final picture. The JIM appr...
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We present a new technique to produce composite images called Puzzle Image Mosaic (PIM). The method is inspired by Jigsaw Image Mosaic (JIM), where image tiles of arbitrary shape are used to compose the final picture. The JIM approach leads to impressive results, but the required computation time is high. We propose an algorithm that produces good results in lower time. The technique takes advantage from recent results about data structures aimed to optimize proximity queries. Experimental results prove the soundness of our method.
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摘要 :
We present a new technique to produce composite images called Puzzle Image Mosaic (PIM). The method is inspired by Jigsaw Image Mosaic (JIM), where image tiles of arbitrary shape are used to compose the final picture. The JIM appr...
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We present a new technique to produce composite images called Puzzle Image Mosaic (PIM). The method is inspired by Jigsaw Image Mosaic (JIM), where image tiles of arbitrary shape are used to compose the final picture. The JIM approach leads to impressive results, but the required computation time is high. We propose an algorithm that produces good results in lower time. The technique takes advantage from recent results about data structures aimed to optimize proximity queries. Experimental results prove the soundness of our method.
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