Results 1 - 10 of 14,403

The secrets of salient object segmentation

by Yin Li , Xiaodi Hou , Christof Koch , James M Rehg , Alan L Yuille - In Computer Vision and Pattern Recognition (CVPR), IEEE Conference on
"... Abstract: In this paper we provide an extensive evaluation of fixation prediction and salient object segmentation algorithms as well as statistics of major datasets. Our analysis identifies serious design flaws of existing salient object benchmarks, called the dataset design bias, by over emphasisi ..."
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Abstract: In this paper we provide an extensive evaluation of fixation prediction and salient object segmentation algorithms as well as statistics of major datasets. Our analysis identifies serious design flaws of existing salient object benchmarks, called the dataset design bias, by over

Shape Sharing for Object Segmentation

by Jaechul Kim, Kristen Grauman , 2012
"... We introduce a category-independent shape prior for object segmentation. Existing shape priors assume class-specific knowledge, and thus are restricted to cases where the object class is known in advance. The main insight of our approach is that shapes are often shared between objects of different ..."
Abstract - Cited by 15 (0 self) - Add to MetaCart
We introduce a category-independent shape prior for object segmentation. Existing shape priors assume class-specific knowledge, and thus are restricted to cases where the object class is known in advance. The main insight of our approach is that shapes are often shared between objects

Shape guided object segmentation

by Eran Borenstein - In Proc. CVPR , 2006
"... We construct a Bayesian model that integrates topdown with bottom-up criteria, capitalizing on their relative merits to obtain figure-ground segmentation that is shape-specific and texture invariant. A hierarchy of bottom-up segments in multiple scales is used to construct a prior on all possible fi ..."
Abstract - Cited by 53 (0 self) - Add to MetaCart
figure-ground segmentations of the image. This prior is used by our top-down part to query and detect object parts in the image using stored shape templates. The detected parts are integrated to produce a global approximation for the object’s shape, which is then used by an inference algorithm to produce

Hierarchical Video Object Segmentation

by Junliang Xing, Haizhou Ai, Shihong Lao
"... Abstract—In this paper, we propose a general video object segmentation framework which views object segmentation from a unified Bayesian perspective and optimizes the MAP formulated problem in a progressive manner. Based on object detection and tracking results, a three-level hierarchical video obje ..."
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Abstract—In this paper, we propose a general video object segmentation framework which views object segmentation from a unified Bayesian perspective and optimizes the MAP formulated problem in a progressive manner. Based on object detection and tracking results, a three-level hierarchical video

From Logo to Object Segmentation

by Fanman Meng, Hongliang Li, Senior Member, Guanghui Liu, King Ngi Ngan
"... Abstract—This paper proposes a method to segment object from the web images using logo detection. The method consists of three steps. In the first step, the logos are located from the original im-ages by SIFT matching. Based on the logo location and the ob-ject shape model, the second step extracts ..."
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Abstract—This paper proposes a method to segment object from the web images using logo detection. The method consists of three steps. In the first step, the logos are located from the original im-ages by SIFT matching. Based on the logo location and the ob-ject shape model, the second step extracts

Object Segmentation Object Recognition Visual Working Memory

by Mary J. Bravo, Hany Farid
"... Object segmentation by top-down processes ..."
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Object segmentation by top-down processes

SUPERVISED VIDEO OBJECT SEGMENTATION

by Using A Small, Number Of Interactions
"... In this paper, a supervised video object segmentation algorithm using a small number of interactions is proposed. The proposed algorithm is composed of three steps: semi-automatic first frame segmentation, automatic object tracking and boundary refinement. Homogeneous region segmentation is performe ..."
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In this paper, a supervised video object segmentation algorithm using a small number of interactions is proposed. The proposed algorithm is composed of three steps: semi-automatic first frame segmentation, automatic object tracking and boundary refinement. Homogeneous region segmentation

Video Object Segmentation

by Chia-cheun Liang, Jing-ying Chang, Liang-gee Chen
"... A coherence-oriented run-processing method and its hardware architecture is proposed for multiple widely-used techniques in video object segmentation algorithms including connected component labeling, binary morphology, seeded region growing and bitwise operations of binary masks. Experimented resul ..."
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A coherence-oriented run-processing method and its hardware architecture is proposed for multiple widely-used techniques in video object segmentation algorithms including connected component labeling, binary morphology, seeded region growing and bitwise operations of binary masks. Experimented

Key-segments for video object segmentation

by Yong Jae Lee, Jaechul Kim, Kristen Grauman - In ICCV , 2011
"... We present an approach to discover and segment foreground object(s) in video. Given an unannotated video sequence, the method first identifies object-like regions in any frame according to both static and dynamic cues. We then compute a series of binary partitions among those candidate “key-segments ..."
Abstract - Cited by 60 (3 self) - Add to MetaCart
We present an approach to discover and segment foreground object(s) in video. Given an unannotated video sequence, the method first identifies object-like regions in any frame according to both static and dynamic cues. We then compute a series of binary partitions among those candidate “key-segments

Minimal Surfaces Based Object Segmentation

by Vincent Caselles, Ron Kimmel, Guillermo Sapiro, Catalina Sbert - IEEE Transactions on Pattern Analysis and Machine Intelligence , 1997
"... A geometric approach for 3D object segmentation and representation is presented. The segmentation is obtained by deformable surfaces moving towards the objects to be detected in the 3D image. The model is based on curvature motion and the computation of surfaces with minimal areas, better known as m ..."
Abstract - Cited by 75 (13 self) - Add to MetaCart
A geometric approach for 3D object segmentation and representation is presented. The segmentation is obtained by deformable surfaces moving towards the objects to be detected in the 3D image. The model is based on curvature motion and the computation of surfaces with minimal areas, better known
Results 1 - 10 of 14,403