Sentence examples for scene region from inspiring English sources

Another noteworthy problem is that for some MSPs, even they are shooting the similar scene, the overlapped scene region among their images is quite small, due to the differences in viewpoints.

When observing a sequence of video frames, one may distinguish between stationary scene regions that do not change over time and dynamic scene regions containing moving objects (nonstationary regions).

In this paper, we propose a hierarchical semantic segmentation method which aims at understanding both scene regions and objects.

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.

This stereo imagery contains more image noise and a significant increase in untextured scene regions that (compared to the stereo imagery of Sections 4.1 and 4.3) can be challenging to some stereo correspondence approaches.

Such measures are bias towards the correct disparity calculation of large textured scene regions (e.g. background) at the expense of the clarity of smaller, closer non-textured objects (e.g. other vehicles/pedestrians).

13 The only exception was luminance, for which there was a slight increase/decrease in mean luminance for image patches in upper/lower scene regions, respectively (Fig. S1).

This paper introduces a new analysis approach to assess quantitatively the extent to which image features predict the probability with which scene regions are selected for fixation.

A more informative approach would be one that distinguishes between fixated and nonfixated scene regions and directly describes the relationship between fixation probability and local feature values on a continuous scale.

The negative quadratic coefficient in the luminance-only GLMM suggested that fixation probability is maximal for image patches with medium-luminance, and is considerably reduced for both very dark and very bright scene regions.

A contrast was calculated of the scene conditions relative to the object baselines ([perceive scenes + construct scenes + maintain perceived scenes + maintain constructed scenes] − [perceive objects + construct objects + maintain perceived objects + maintain constructed objects]), which revealed activation of a priori scene regions in addition to a large area of visual cortex (Fig. 2, Table 1).