Geodesic-based Salient Object Detection
Saliency detection has been an intuitive way to provide useful cues for object detection and segmentation, as desired for many vision and graphics applications. In this paper, we provided a robust method for salient object detection and segmentation. Other than using various pixel-level contrast definitions, we exploited global image structures and proposed a new geodesic method dedicated for salient object detection. In the proposed approach, a new geodesic scheme, namely geodesic tunneling is proposed to tackle with textures and local chaotic structures. With our new geodesic approach, a geodesic saliency map is estimated in correspondence to spatial structures in an image. Experimental evaluation on a salient object benchmark dataset validated that our algorithm consistently outperformed a number of the state-of-art saliency methods, yielding higher precision and better recall rates. With the robust saliency estimation, we also present an unsupervised hierarchical salient object cut scheme simply using adaptive saliency thresholding, which attained the highest score in our F-measure test. We also applied our geodesic cut scheme to a number of image editing tasks as demonstrated in additional experiments.
Code (0)
등록된 구현이 없습니다.
Tasks
Objectobject-detectionObject DetectionRGB Salient Object DetectionSaliency DetectionSaliency PredictionSalient Object DetectionSimilar Papers 제목 키워드 기반
Robust Saliency Detection via Fusing Foreground and Background Priors
Automatic Salient object detection has received tremendous attention from research community and has been an increasingly important tool in many computer vision tasks. This paper proposes a novel bottom-up salient object…
object-detectionObject DetectionRGB Salient Object DetectionSaliency Detection+1Automatic Salient Object Detection for Panoramic Images Using Region Growing and Fixation Prediction Model
Almost all previous works on saliency detection have been dedicated to conventional images, however, with the outbreak of panoramic images due to the rapid development of VR or AR technology, it is becoming more challeng…
Density Estimationobject-detectionObject DetectionRGB Salient Object Detection+2Saliency-Aware Geodesic Video Object Segmentation
We introduce an unsupervised, geodesic distance based, salient video object segmentation method. Unlike traditional methods, our method incorporates saliency as prior for object via the computation of robust geodesic mea…
ObjectSegmentationSemantic SegmentationVideo Object Segmentation+2Weakly Supervised Learning for Salient Object Detection
Recent advances in supervised salient object detection has resulted in significant performance on benchmark datasets. Training such models, however, requires expensive pixel-wise annotations of salient objects. Moreover,…
Objectobject-detectionObject DetectionRGB Salient Object Detection+3Salient Object Detection for Images Taken by People With Vision Impairments
Salient object detection is the task of producing a binary mask for an image that deciphers which pixels belong to the foreground object versus background. We introduce a new salient object detection dataset using images…
Objectobject-detectionObject DetectionSalient Object Detection