Sentence examples for scene level from inspiring English sources

The computer graphics approach includes novel techniques of 3D geometry estimation, illumination field recovery, and scene reconstruction to detect inconsistency at the scene level like shadows, shading, and geometry.

In the scene level, different colors indicate different categories.

In the scene level, we use a feature-based MRF model to recognize the scene categories.

This paper proposes the use of video scene identification and classification for traffic modeling at the scene level in order to improve resource allocation and user QoE in GEO satellite networks.

In this paper, we propose a method of hierarchical semantic segmentation, including scene level and object level, which aims at labeling both scene regions and objects in an image.

On the "scene" level of abstraction, the detection of scene similarity/overlap among videos provides a shared context among visual data that is robust to a certain class of scene dynamic content, e.g., we can associate different events recorded in a common setting through background co-occurrence (see Fig. 10).

The resulting tracker is primarily geared towards scene-level video surveillance applications.

Our results also reveal the spatially variable performance of the multispectral water index and indicate the limitation of using scene-level cloud cover to screen satellite images.

Based on this framework we can integrate multiple features and design embeddings for large scale recognition directly in the scene-level space.

In contrast, the semantic multinomial (SMN) represents patches directly in the scene-level semantic space, which leads to ambiguity when aggregated to a global image representation.

The final scene-level labeling is adjusted with the object-level labeling, generating a more precise scene-level result.