共查询到10条相似文献,搜索用时 328 毫秒
1.
The technique of relevance feedback has been introduced to content-based 3D model retrieval, however, two essential issues
which affect the retrieval performance have not been addressed. In this paper, a novel relevance feedback mechanism is presented,
which effectively makes use of strengths of different feature vectors and perfectly solves the problem of small sample and
asymmetry. During the retrieval process, the proposed method takes the user’s feedback details as the relevant information
of query model, and then dynamically updates two important parameters of each feature vector, narrowing the gap between high-level
semantic knowledge and low-level object representation. The experiments, based on the publicly available 3D model database
Princeton Shape Benchmark (PSB), show that the proposed approach not only precisely captures the user’s semantic knowledge,
but also significantly improves the retrieval performance of 3D model retrieval. Compared with three state-of-the-art query
refinement schemes for 3D model retrieval, it provides superior retrieval effectiveness only with a few rounds of relevance
feedback based on several standard measures.
相似文献
Biao LengEmail: |
2.
3.
The comparison of digital images to determine their degree of similarity is one of the fundamental problems of computer vision.
Many techniques exist which accomplish this with a certain level of success, most of which involve either the analysis of
pixel-level features or the segmentation of images into sub-objects that can be geometrically compared. In this paper we develop
and evaluate a new variation of the pixel feature and analysis technique known as the color correlogram in the context of
a content-based image retrieval system. Our approach is to extend the autocorrelogram by adding multiple image features in
addition to color. We compare the performance of each index scheme with our method for image retrieval on a large database
of images. The experiment shows that our proposed method gives a significant improvement over histogram or color correlogram
indexing, and it is also memory-efficient.
相似文献
Peter YoonEmail: |
4.
Robert S. Lee Chin-Wan Chung Seok-Lyong Lee Sang-Hee Kim 《Multimedia Tools and Applications》2008,40(3):385-407
Relevance feedback is commonly incorporated into content-based image retrieval systems with the objective of improving retrieval
accuracy via user feedback. One effective method for improving retrieval performance is to perform feature re-weighting based
on the obtained feedback. Previous approaches to feature re-weighting via relevance feedback assume the feature data for images
can be represented in fixed-length vectors. However, many approaches are invalidated with the recent development of features
that cannot be represented in fixed-length vectors. In addition, previous approaches use only the information from the set
of images returned in the latest query result for feature re-weighting. In this paper, we propose a feature re-weighting approach
that places no restriction on the representation of feature data and utilizes the aggregate set of images returned over the
iterations of retrieval to obtain feature re-weighting information. The approach analyzes the feature distances calculated
between the query image and the resulting set of images to approximate the feature distances for the entire set of images
in the database. Two-sided confidence intervals are used with the distances to obtain the information for feature re-weighting.
There is no restriction on how the distances are calculated for each feature. This provides freedom for how the feature representations
are structured. The experimental results show the effectiveness of the proposed approach and in comparisons with other work,
it is shown that our approach outperforms previous work.
相似文献
Chin-Wan ChungEmail: |
5.
Socrates Dimitriadis Kostas Marias Stelios C. Orphanoudakis 《Multimedia Tools and Applications》2007,33(1):57-72
Efficient and possibly intelligent image retrieval is an important task, often required in many fields of human activity.
While traditional database indexing techniques exhibit a remarkable performance in textual information retrieval current research
in content-based image retrieval is focused on developing novel techniques that are biologically motivated and efficient.
It is well known that humans have a remarkable ability to process visual information and to handle the volume and complexity
of such information quite efficiently. In this paper, we present a content-based image retrieval platform that is based on
a multi-agent architecture. Each agent is responsible for assessing the similarity of the query image to each candidate image
contained in a collection based on a specific primitive feature and a corresponding similarity criterion. The outputs of various
agents are integrated using one of several voting schemes supported by the system. The system’s performance has been evaluated
using various collections of images, as well as images obtained in specific application domains such as medical imaging. The
initial evaluation has yielded very promising results.
相似文献
Stelios C. OrphanoudakisEmail: |
6.
This paper presents research on a robust technique for texture-based image retrieval in multimedia museum collections. The
aim is to be able to use a query image patch containing a single texture to retrieve images containing an area with similar
texture to that in the query. The feature extractor used to build the feature vectors is based on an improved version of the
discrete wavelet frames (DWF), proposed elsewhere. In order to utilise the feature extractor on real scene image datasets,
a block-oriented decomposition technique, termed the multiscale sub-image matching method, is presented. The multiscale method,
together with the DWF, provide an efficient content-based retrieval technique without the need for segmentation. The algorithms
are tested on a range of databases of texture images as well as on real museum image collections. Promising results are reported.
相似文献
Mohammad Faizal Ahmad FauziEmail: |
7.
A novel pose estimation algorithm is put forward in this paper. Given the points on an object and the convex regions in which
the correspondent image points lie, the concrete values of position and orientation (t and R) between the object and the camera are found based on a points to regions correspondence. The unit quaternion representation
of rotation matrix and convex Linear Matrix Inequalities (LMI) optimization methods are used to estimate the pose. By loosening
the requirement of precise point to point correspondence and using convex LMI formulations, this algorithm provides a more
robust and faster pose estimation method. The effect of this method is verified by simulation and laboratory experiment results.
相似文献
Zhen QiEmail: |
8.
This work proposes a method to decompose the kernel within-class eigenspace into two subspaces: a reliable subspace spanned
mainly by the facial variation and an unreliable subspace due to limited number of training samples. A weighting function
is proposed to circumvent undue scaling of eigenvectors corresponding to the unreliable small and zero eigenvalues. Eigenfeatures
are then extracted by the discriminant evaluation in the whole kernel space. These efforts facilitate a discriminative and
stable low-dimensional feature representation of the face image. Experimental results on FERET, ORL and GT databases show
that our approach consistently outperforms other kernel based face recognition methods.
相似文献
Alex KotEmail: |
9.
Cheng-Chin Chiang Jyun-Yue Wu Mau-Tsuen Yang Wen-Kai Tai 《Multimedia Tools and Applications》2009,41(1):27-53
Query refinement and feature re-weighting are the two core techniques underlying the relevance feedback of content-based image
retrieval. Most existing relevance feedback mechanisms generally model the user’s query target with a single query point and
weight each extracted feature with a single importance factor. A designed estimation procedure then estimates the best query
point and all importance factors by optimizing a formulated criterion which measures the goodness of the estimation. This
formulated criterion simultaneously encapsulates all positive and negative examples supplied from the user’s feedback. Under
such formulation, the positive and negative examples may contribute contradictorily to the criterion and sometimes may introduce
higher difficulty in attaining a good estimation. In this paper, we propose a different statistical formulation to estimate
independently two pairs of query points and feature weights from the positive examples and negative examples, respectively.
These two pairs then define the likelihood ratio, a criterion term used to rank the relevance of all database images. This
approach simplifies the criterion formulation and also avoids the mutual impeditive influence between positive examples and
negative examples. The experimental results demonstrate that the proposed approach outperforms some other related approaches.
相似文献
Wen-Kai TaiEmail: |
10.
This paper proposes an appearance generative mixture model based on key frames for meanshift tracking. Meanshift tracking
algorithm tracks an object by maximizing the similarity between the histogram in tracking window and a static histogram acquired
at the beginning of tracking. The tracking therefore could fail if the appearance of the object varies substantially. In this
paper, we assume the key appearances of the object can be acquired before tracking and the manifold of the object appearance
can be approximated by piece-wise linear combination of these key appearances in histogram space. The generative process is
described by a Bayesian graphical model. An Online EM algorithm is proposed to estimate the model parameters from the observed
histogram in the tracking window and to update the appearance histogram. We applied this approach to track human head motion
and to infer the head pose simultaneously in videos. Experiments verify that our online histogram generative model constrained
by key appearance histograms alleviates the drifting problem often encountered in tracking with online updating, that the
enhanced meanshift algorithm is capable of tracking object of varying appearances more robustly and accurately, and that our
tracking algorithm can infer additional information such as the object poses.
Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.
相似文献
Jilin Tu (Corresponding author)Email: |
Hai TaoEmail: |
Thomas HuangEmail: |