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Article
Putting the User in the Loop for Image-Based Modeling
We refer to the task of recovering the 3D structure of an object or a scene using 2D images as image-based modeling. In this paper, we formulate the task of recovering the 3D structure as a discrete optimizati...
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Chapter and Conference Paper
Tensor Total-Variation Regularized Deconvolution for Efficient Low-Dose CT Perfusion
Acute brain diseases such as acute stroke and transit ischemic attacks are the leading causes of mortality and morbidity worldwide, responsible for 9% of total death every year. ‘Time is brain’ is a widely acc...
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Chapter and Conference Paper
Tissue-Specific Sparse Deconvolution for Low-Dose CT Perfusion
Sparse perfusion deconvolution has been recently proposed to effectively improve the image quality and diagnostic accuracy of low-dose perfusion CT by extracting the complementary information from the high-dos...
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Chapter and Conference Paper
Beyond Spatial Pyramid Matching: Spatial Soft Voting for Image Classification
Recently, spatial partitioning approaches such as spatial pyramid matching (SPM) are commonly used in image classification to collect the global and local features of the images. They divide the input image in...
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Chapter and Conference Paper
Combining Monocular Geometric Cues with Traditional Stereo Cues for Consumer Camera Stereo
This paper presents an algorithm for considering both stereo cues and structural priors to obtain a geometrically representative depth map from a narrow baseline stereo pair. We use stereo pairs captured with ...
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Chapter and Conference Paper
Sparsity-Based Deconvolution of Low-Dose Perfusion CT Using Learned Dictionaries
Computational tomography perfusion (CTP) is an important functional imaging modality in the evaluation of cerebrovascular diseases, such as stroke and vasospasm. However, the post-processed parametric maps of ...
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Chapter and Conference Paper
Segmentation of Liver Tumor Using Efficient Global Optimal Tree Metrics Graph Cuts
We propose a novel approach that applies global optimal tree-metrics graph cuts algorithm on multi-phase contrast enhanced contrast enhanced MRI for liver tumor segmentation. To address the difficulties caused...
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Chapter and Conference Paper
A Generic Model to Compose Vision Modules for Holistic Scene Understanding
The problem of holistic scene understanding involves many vision tasks such as depth estimation, scene categorization, event categorization, etc. Each of these tasks explores some aspects of the scene but, the...
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Chapter and Conference Paper
Spatio-Temporal Phrases for Activity Recognition
The local feature based approaches have become popular for activity recognition. A local feature captures the local movement and appearance of a local region in a video, and thus can be ambiguous; e.g., it can...
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Chapter and Conference Paper
Learning to Segment a Video to Clips Based on Scene and Camera Motion
In this paper, we present a novel learning-based algorithm for temporal segmentation of a video into clips based on both camera and scene motion, in particular, based on combinations of static vs. dynamic came...
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Chapter and Conference Paper
iModel: Interactive Co-segmentation for Object of Interest 3D Modeling
We present an interactive system to create 3D models of objects of interest in their natural cluttered environments.
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Article
Interactively Co-segmentating Topically Related Images with Intelligent Scribble Guidance
We present an algorithm for Interactive Co-segmentation of a foreground object from a group of related images. While previous works in co-segmentation have focussed on unsupervised co-segmentation, we use success...
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Book
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Book and Conference Proceedings
Advances in Multimedia Modeling
17th International Multimedia Modeling Conference, MMM 2011, Taipei, Taiwan, January 5-7, 2011, Proceedings, Part I
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Book and Conference Proceedings
Advances in Multimedia Modeling
17th International Multimedia Modeling Conference, MMM 2011, Taipei, Taiwan, January 5-7, 2011, Proceedings, Part II
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Chapter
Introduction
In this chapter, we introduce the problem of co-segmentation and survey some recent algorithms for co-segmentation. We organize these algorithms along two dimensions – degree of supervision and scalability. Fi...
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Chapter
Applications
The task of segmenting out the foreground from a group of topically related images lends itself to a number of interesting applications. One such application is creating a photo collage. We can imagine a scena...
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Chapter
Future of Co-segmentation
Co-segmentation is a new topic which has only been recently introduced into the computer vision community. In Chapter 2 we have discussed the interactive co-segmentation algorithm in detail and in Chapter 3 we...
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Chapter
An Approach to Interactive Co-segmentation
In this chapter, we describe in detail our approach to interactive cosegmentation. We formulate the task as an energy minimization problem across all related images in a group. The energies across images are t...
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Article
Open AccessSubgraphs Matching-Based Side Information Generation for Distributed Multiview Video Coding
We adopt constrained relaxation for distributed multiview video coding (DMVC). The novel framework integrates the graph-based segmentation and matching to generate interview correlated side information without...
