Tools
Sorted by:
Try your query at:
 |
 |
 |
 |
 |
 |
Results 1 - 10
of
3,218
Harmonium Models for Video Classification
, 2008
"... Accurate and efficient video classification demands the fusion of multimodal information and the use of intermediate representations. Combining the two ideas into one framework, we propose a series of probabilistic models for video representation and classification using intermediate semantic repres ..."
Abstract
-
Cited by 3 (0 self)
- Add to MetaCart
Accurate and efficient video classification demands the fusion of multimodal information and the use of intermediate representations. Combining the two ideas into one framework, we propose a series of probabilistic models for video representation and classification using intermediate semantic
News Video Classification
"... Abstract- News video concepts based event classification is a system,where the classification of videos will be done on the basis of video contents. For such classification first key frames will be extracted from the video and these key frames will be processed for Feature Extraction. In this system ..."
Abstract
- Add to MetaCart
Abstract- News video concepts based event classification is a system,where the classification of videos will be done on the basis of video contents. For such classification first key frames will be extracted from the video and these key frames will be processed for Feature Extraction
Automatic video classification: A survey of the literature
- IEEE Transactions on Systems, Man, and Cybernetics, Part C
"... Abstract—There is much video available today. To help viewers find video of interest, work has begun on methods of automatic video classification. In this paper, we survey the video classification literature. We find that features are drawn from three modalities–text, audio, and visual–and that a la ..."
Abstract
-
Cited by 45 (2 self)
- Add to MetaCart
Abstract—There is much video available today. To help viewers find video of interest, work has begun on methods of automatic video classification. In this paper, we survey the video classification literature. We find that features are drawn from three modalities–text, audio, and visual–and that a
Sports video classification using HMMs
- in Proc. IEEE Int. Conf. Multimedia & Expo (ICME
, 2003
"... In this paper we address the problem of sports video classification Using Hidden Markov Models (HMMs). For each sports genre, we construct two HMMs representing motion and color features respectively. The observation sequences generated from the principal motion direction and the principal color of ..."
Abstract
-
Cited by 14 (0 self)
- Add to MetaCart
In this paper we address the problem of sports video classification Using Hidden Markov Models (HMMs). For each sports genre, we construct two HMMs representing motion and color features respectively. The observation sequences generated from the principal motion direction and the principal color
Semantic Video Classification with Insufficient Labeled
- Samples”, SPIE: Storage and Retrieval of Media Database
"... To support more effective video retrieval at semantic level, we introduce a novel framework to achieve semantic video classification. This novel framework includes: (a) A semantic-senstive video content representation framework via principal video shots to enhance the quality of features (i.e., the ..."
Abstract
-
Cited by 1 (0 self)
- Add to MetaCart
To support more effective video retrieval at semantic level, we introduce a novel framework to achieve semantic video classification. This novel framework includes: (a) A semantic-senstive video content representation framework via principal video shots to enhance the quality of features (i
Learning frame relevance for video classification
- In ACM MM
, 2011
"... Traditional video classification methods typically require a large number of labeled training video frames to achieve sat-isfactory performance. However, in the real world, we usu-ally only have sufficient labeled video clips (such as tagged online videos) but lack labeled video frames. In this pape ..."
Abstract
-
Cited by 2 (2 self)
- Add to MetaCart
Traditional video classification methods typically require a large number of labeled training video frames to achieve sat-isfactory performance. However, in the real world, we usu-ally only have sufficient labeled video clips (such as tagged online videos) but lack labeled video frames
Learning realistic human actions from movies
- IN: CVPR.
, 2008
"... The aim of this paper is to address recognition of natural human actions in diverse and realistic video settings. This challenging but important subject has mostly been ignored in the past due to several problems one of which is the lack of realistic and annotated video datasets. Our first contribut ..."
Abstract
-
Cited by 738 (48 self)
- Add to MetaCart
next turn to the problem of action classification in video. We present a new method for video classification that builds upon and extends several recent ideas including local space-time features, space-time pyramids and multichannel non-linear SVMs. The method is shown to improve state
Large-scale Video Classification with Convolutional Neural Networks
"... Convolutional Neural Networks (CNNs) have been es-tablished as a powerful class of models for image recog-nition problems. Encouraged by these results, we pro-vide an extensive empirical evaluation of CNNs on large-scale video classification using a new dataset of 1 million YouTube videos belonging ..."
Abstract
-
Cited by 68 (5 self)
- Add to MetaCart
Convolutional Neural Networks (CNNs) have been es-tablished as a powerful class of models for image recog-nition problems. Encouraged by these results, we pro-vide an extensive empirical evaluation of CNNs on large-scale video classification using a new dataset of 1 million YouTube videos belonging
Voting based Video Classification Using Clustering and Learning
"... In this paper, we propose video classification using lin-ear manifolds (affine subspaces). In our method, we rep-resent videos belonging to a same class by several linear manifolds using k-varieties clustering. When a test video is given, each frame of it votes for the class to which its nearest lin ..."
Abstract
- Add to MetaCart
In this paper, we propose video classification using lin-ear manifolds (affine subspaces). In our method, we rep-resent videos belonging to a same class by several linear manifolds using k-varieties clustering. When a test video is given, each frame of it votes for the class to which its nearest
Results 1 - 10
of
3,218
