Sentence examples for scene segmentation from inspiring English sources

Its goal is to jointly perform scene segmentation and multiclass object-level segment recognition in digital images.

This section briefly summarizes some relevant recent work on scene segmentation and semantic labeling.

The approach is compared to other two significant natural scene segmentation methods, achieving better results in a global evaluation.

For 3D perception of objects on planar surfaces, we develop scene segmentation methods that process depth images in real-time at high frame rates.

This paper presents a method that combines radar and monocular vision for ground modeling and scene segmentation by a mobile robot operating in outdoor environments.

Another approach takes advantage of the image patch and spatial prior [10] for attaining better scene segmentation.

Secondly, based on the context assessing results, under the BoF framework, we design unified object representations that incorporate the object appearance and contextual information from multiple spatial levels without the need of prior scene segmentations or context annotations.

All database videos have been annotated with respect to (mono- and multimodal) sensory and semantic saliency (in a binary mode), including scene and shot segmentation, by three annotators in separate runs for each individual saliency layer, starting with audio annotation, followed by visual, audiovisual, semantics, and the annotation of the informative segments.

This task works with a combination of analysis and processing for movie frames, shots, scenes, segmentation and textual description.

For each scene, the segmentations of the individual input image modalities were used to derive a joint reference ("gold standard") contour image that represents the visually most salient details from both of these modalities and for that particular scene.

A major limitation of our algorithm is that for the very complex scenes, the object segmentation accuracy may decrease.