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124
ClassView: Hierarchical Video Shot Classification, Indexing, and Accessing
- IEEE TRANS. ON MULTIMEDIA
, 2004
"... Recent advances in digital video compression and networks have made video more accessible than ever. However, the existing content-based video retrieval systems still suffer from the following problems. 1 ) Semantics---sensitive video classification problem because of the semantic gap between low-le ..."
Abstract
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Cited by 42 (4 self)
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View, to make some advances toward more efficient video database indexing and access. 1) A hierarchical semantics-sensitive video classifier is proposed to shorten the semantic gap. The hierarchical tree structure of the semantics-sensitive video classifier is derived from the domain-dependent concept hierarchy
Concept-Oriented Indexing of Video Databases: Toward Semantic Sensitive Retrieval and Browsing
- IEEE TRANS. ON IMAGE PROCESSING
, 2004
"... Digital video now plays an important role in medical education, health care, telemedicine and other medical applications. Several content-based video retrieval (CBVR) systems have been proposed in the past, but they still suffer from the following challenging problems: semantic gap, semantic video ..."
Abstract
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Cited by 34 (6 self)
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concept modeling, semantic video classification, and concept-oriented video database indexing and access. In this paper, we propose a novel framework to make some advances toward the final goal to solve these problems. Specifically, the framework includes: 1) a semantic-sensitive video content
2009b. Spatio-temporal relationship match: Video structure comparison for recognition of complex human activities
- In IEEE International Conference on Computer Vision (ICCV
"... Human activity recognition is a challenging task, especially when its background is unknown or changing, and when scale or illumination differs in each video. Approaches utilizing spatio-temporal local features have proved that they are able to cope with such difficulties, but they mainly focused on ..."
Abstract
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Cited by 112 (9 self)
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similarity between sets of features extracted from two videos. Our match hierarchically considers spatio-temporal relationships among feature points, thereby enabling detection and localization of complex non-periodic activities. In contrast to previous approaches to ‘classify ’ videos, our approach
AUTOMATIC VIDEO GENRE CATEGORIZATION USING HIERARCHICAL SVM
, 2006
"... This paper presents an automatic video genre categorization scheme based on the hierarchical ontology on video genres. Ten computable spatio-temporal features are extracted to distinguish the different genres using a hierarchical Support Vector Machines (SVM) classifier built by cross-validation, wh ..."
Abstract
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Cited by 15 (1 self)
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This paper presents an automatic video genre categorization scheme based on the hierarchical ontology on video genres. Ten computable spatio-temporal features are extracted to distinguish the different genres using a hierarchical Support Vector Machines (SVM) classifier built by cross
Feature Reduction and Hierarchy of Classifiers for Fast Object Detection in Video Images
, 2001
"... We present a two-step method to speed-up object detection systems in computer vision that use Support Vector Machines (SVMs) as classifiers. In a first step we perform feature reduction by choosing relevant image features according to a measure derived from statistical learning theory. In a second s ..."
Abstract
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Cited by 40 (4 self)
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We present a two-step method to speed-up object detection systems in computer vision that use Support Vector Machines (SVMs) as classifiers. In a first step we perform feature reduction by choosing relevant image features according to a measure derived from statistical learning theory. In a second
Hierarchical Probabilistic Models for Video Object Segmentation and Tracking
"... When tracking and segmenting semantic video objects, different forms of representational model can be used to find the object region on a per-frame basis. We propose a novel hierarchical technique using parametric models to describe the appearance and location of an object and then use nonparametric ..."
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When tracking and segmenting semantic video objects, different forms of representational model can be used to find the object region on a per-frame basis. We propose a novel hierarchical technique using parametric models to describe the appearance and location of an object and then use
Illumination Invariant Video Segmentation by Hierarchical Robust Thresholding
, 1998
"... Many methods for video segmentation rely upon the setting and tuning of thresholds for classifying interframe distances under various difference measures. An approach that has been used with some success has been to establish statistical measures for each new video and identify camera cuts as differ ..."
Abstract
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Cited by 7 (3 self)
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Many methods for video segmentation rely upon the setting and tuning of thresholds for classifying interframe distances under various difference measures. An approach that has been used with some success has been to establish statistical measures for each new video and identify camera cuts
Video Object Segmentation by Hierarchical Localized Classification of Regions
"... Abstract—Video Object Segmentation (VOS) is to cut out a selected object from video sequences, where the main difficulties are shape deformation, appearance variations and background clutter. To cope with these difficulties, we propose a novel method, named as Hierarchical Localized Classification o ..."
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Abstract—Video Object Segmentation (VOS) is to cut out a selected object from video sequences, where the main difficulties are shape deformation, appearance variations and background clutter. To cope with these difficulties, we propose a novel method, named as Hierarchical Localized Classification
Hierarchical probabilistic models for video object segmentation and tracking
- in: International Conference on Pattern Recognition
"... The Problem: The goal of segmentation and tracking video objects in generic scenes is to segment the objects accurately and consistently depending on a set of semantics defined. Methods previously applied to this problem can be divided primarily into region-based or boundary-based methods. These two ..."
Abstract
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Cited by 2 (0 self)
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and choice of classifier is dependent on the application and/or semantics defined. Motivation: Semantic video objects with regard to the human visual system often have a complex underlying probability density function within the image feature space and hence previous approaches to this problem have applied
Video Character Recognition Through Hierarchical Classification a
"... Abstract — We present a new video character recognition method based on hierarchical classification. In the first step, we propose a method for character segmentation of the text line detected by the text detection method. The segmentation algorithm uses dynamic programming to find least-cost paths ..."
Abstract
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Abstract — We present a new video character recognition method based on hierarchical classification. In the first step, we propose a method for character segmentation of the text line detected by the text detection method. The segmentation algorithm uses dynamic programming to find least-cost paths
Results 1 - 10
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124
