JOURNAL ARTICLE

Graph Construction for Salient Object Detection in Videos

Abstract

Recently many graph-based salient region/object detection methods have been developed. They are rather effective for still images. However, little attention has been paid to salient region detection in videos. This paper addresses salient region detection in videos. A unified approach towards graph construction for salient object detection in videos is proposed. The proposed method combines static appearance and motion cues to construct graph, enabling a direct extension of original graph based salient region detection to video processing. To maintain coherence in both intra- and inter-frames, a spatial-temporal smoothing operation is proposed on a structured graph derived from consecutive frames. The effectiveness of the proposed method is tested and validated using seven videos from two video datasets.

Keywords:
Salient Computer science Graph Smoothing Artificial intelligence Computer vision Object detection Pattern recognition (psychology) Theoretical computer science

Metrics

9
Cited By
0.96
FWCI (Field Weighted Citation Impact)
23
Refs
0.81
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Visual Attention and Saliency Detection
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Gaze Tracking and Assistive Technology
Physical Sciences →  Computer Science →  Human-Computer Interaction

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