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Sample-Based Vegetation Distribution Information Synthesis.

Xu C, Yang G, Yang M - PLoS ONE (2015)

Bottom Line: This pattern, which represents a local feature in the distribution and occurs repeatedly in the forest, is in line with the "locality" and "static" characteristics in the "texture data", making it possible to use a sample-based texture synthesis strategy to build the distribution.A sample forest stand is obtained first and recorded as a two-dimensional vector-element distribution pattern.The synthesized distribution pattern resembles the sample pattern in the distribution features.

View Article: PubMed Central - PubMed

Affiliation: School of Information Science and Technology, Beijing Forestry University, Beijing, China; School of Animation and Digital Arts, Communication University of China, Beijing, China.

ABSTRACT
In constructing and visualizing a virtual three-dimensional forest scene, we must first obtain the vegetation distribution, namely, the location of each plant in the forest. Because the forest contains a large number of plants, the distribution of each plant is difficult to obtain from actual measurement methods. Random approaches are used as common solutions to simulate a forest distribution but fail to reflect the specific biological arrangements among types of plants. Observations show that plants in the forest tend to generate particular distribution patterns due to growth competition and specific habitats. This pattern, which represents a local feature in the distribution and occurs repeatedly in the forest, is in line with the "locality" and "static" characteristics in the "texture data", making it possible to use a sample-based texture synthesis strategy to build the distribution. We propose a vegetation distribution data generation method that uses sample-based vector pattern synthesis. A sample forest stand is obtained first and recorded as a two-dimensional vector-element distribution pattern. Next, the large-scale vegetation distribution pattern is synthesized automatically using the proposed vector pattern synthesis algorithm. The synthesized distribution pattern resembles the sample pattern in the distribution features. The vector pattern synthesis algorithm proposed in this paper adopts a neighborhood comparison technique based on histogram matching, which makes it efficient and easy to implement. Experiments show that the distribution pattern synthesized with this method can sufficiently preserve the features of the sample distribution pattern, making our method meaningful for constructing realistic forest scenes.

No MeSH data available.


Related in: MedlinePlus

Regular distribution sample synthesis.Left: sample; Middle: synthesized result; Right: 3D forest scene.
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pone.0134009.g009: Regular distribution sample synthesis.Left: sample; Middle: synthesized result; Right: 3D forest scene.

Mentions: We build the 3D model for each type of plant, and position these plant models in the scene according to the distribution information in the 2D vector pattern. By using this manner, we constructed the 3D forest scenes (as shown in the right part of Figs 1 and 9–12).


Sample-Based Vegetation Distribution Information Synthesis.

Xu C, Yang G, Yang M - PLoS ONE (2015)

Regular distribution sample synthesis.Left: sample; Middle: synthesized result; Right: 3D forest scene.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4529179&req=5

pone.0134009.g009: Regular distribution sample synthesis.Left: sample; Middle: synthesized result; Right: 3D forest scene.
Mentions: We build the 3D model for each type of plant, and position these plant models in the scene according to the distribution information in the 2D vector pattern. By using this manner, we constructed the 3D forest scenes (as shown in the right part of Figs 1 and 9–12).

Bottom Line: This pattern, which represents a local feature in the distribution and occurs repeatedly in the forest, is in line with the "locality" and "static" characteristics in the "texture data", making it possible to use a sample-based texture synthesis strategy to build the distribution.A sample forest stand is obtained first and recorded as a two-dimensional vector-element distribution pattern.The synthesized distribution pattern resembles the sample pattern in the distribution features.

View Article: PubMed Central - PubMed

Affiliation: School of Information Science and Technology, Beijing Forestry University, Beijing, China; School of Animation and Digital Arts, Communication University of China, Beijing, China.

ABSTRACT
In constructing and visualizing a virtual three-dimensional forest scene, we must first obtain the vegetation distribution, namely, the location of each plant in the forest. Because the forest contains a large number of plants, the distribution of each plant is difficult to obtain from actual measurement methods. Random approaches are used as common solutions to simulate a forest distribution but fail to reflect the specific biological arrangements among types of plants. Observations show that plants in the forest tend to generate particular distribution patterns due to growth competition and specific habitats. This pattern, which represents a local feature in the distribution and occurs repeatedly in the forest, is in line with the "locality" and "static" characteristics in the "texture data", making it possible to use a sample-based texture synthesis strategy to build the distribution. We propose a vegetation distribution data generation method that uses sample-based vector pattern synthesis. A sample forest stand is obtained first and recorded as a two-dimensional vector-element distribution pattern. Next, the large-scale vegetation distribution pattern is synthesized automatically using the proposed vector pattern synthesis algorithm. The synthesized distribution pattern resembles the sample pattern in the distribution features. The vector pattern synthesis algorithm proposed in this paper adopts a neighborhood comparison technique based on histogram matching, which makes it efficient and easy to implement. Experiments show that the distribution pattern synthesized with this method can sufficiently preserve the features of the sample distribution pattern, making our method meaningful for constructing realistic forest scenes.

No MeSH data available.


Related in: MedlinePlus