30245999
Object Class Recognition Using SNoW with a Part Vocabulary
In this paper we present a novel method for object class recognition. A vocabulary of object parts is automatically constructed from sample images of the object class by AdaBoost. Images are then represented using parts from this vocabulary. Based on this representation, the Sparse Network of Winnows (SNoW) learning architecture is employed to learn to recognize instances of the object class. Experimental results show that the method achieves high recognition accuracy on different data sets, and is highly robust to partial occlusion and background clutter.
17154425
Background Subtraction using Incremental Subspace Learning
Background modeling and subtraction is a basic component of many computer vision and video analysis applications. It has a critical impact on the performance of object tracking and activity analysis. In this paper, we propose an effective and adaptive background modeling and subtraction approach that can deal with dynamic scenes. The proposed approach uses a subspace learning method to model the background and the subspace is updated on-line with a sequential Karhunen-Loeve algorithm. A linear prediction model is also used to make the detection more robust. Experimental results show that the proposed approach is able to model the background and detect moving objects under various type of background scenarios with close to real-time performance.
17672081
A Sub-Vector Weighting Scheme for Image Retrieval with Relevance Feedback
In image retrieval with relevance feedback, feature components are weighted to reflect the high-level concepts, and a user's subjective perception, embodied in the images labelled by the user in the feedback. However, the number of labelled images is often small and the covariance matrix needed for weighting will be singular. For this reason, the commonly used methods discard the mutual correlation among the feature components completely and use a diagonal covariance matrix. In this paper, a sub-vector weighting scheme is proposed. This scheme partitions a multi-dimensional visual feature vector into multiple low-dimensional sub-vectors. The singularity of the covariance matrix for each sub-vector can be avoided due to the lower dimensionality of the sub-vectors. Thus, the mutual correlation in each sub-vector can be retained for weighting and an optimally weighted similarity metric can be applied on each sub-vector. The similarity scores obtained from different sub-vectors are combined, as the final scor...
14309178
A New Rights Processing Method for DRM Systems
There are many solutions and standards about digital rights management(DRM) now. Almost all the solutions used cryptography and rights processing technologies to protect contents. Only legal users can decrypt and enjoy contents under the control of rights information, illegal users are prohibited. Rights processing technologies include rights expression languages (REL), binary encoding method, virtual machine, and so on. ODRL (Open Digital Rights Language) and XrML (eXtensible Markup Language) are all RELs, which express rights based on XML. Broadcasting flag encodes copy control information into binary data block. Marlin DRM uses Plankton virtual machine to process rights information. In this paper, we provided a rights processing method which is based on ASN.1(Abstract Syntax Notation One) syntax and using ASN.1 distinguishable encoding rule (DER) to encode rights information into binary data block. Compared with RELs, this rights processing method uses less bits to express rights information and can save more bandwidth during transmission. And it can express more rights information than broadcast flag.
13235702
Provisioning QoS guarantee by multipath routing and reservation in Ad hoc networks
In this paper, a QoS multipath source routing protocol (QoS-MSR) is proposed for ad hoc networks. It can collect QoS information through route discovery mechanism of multipath source routing (MSR) and establish QoS route with reserved bandwidth. In order to reserve bandwidth efficiently, a bandwidth reservation approach called the multipath bandwidth splitting reservation (MBSR) is presented, under which the overall bandwidth request is split into several smaller bandwidth requests among multiple paths. In simulations, the anthors introduce Insignia, an in-bind signaling system that supports QoS in ad hoc networks, and extend it to multipath Insignia (M-Insignia) with QoS-MSR and MBSR. The results show that QoS-MSR routing protocol with the MBSR algorithm can improve the call admission ratio of QoS traffic, the packet delivery ratio, and the end-to-end delay of both best-effort traffic and QoS traffic. Therefore, QoS-MSR with MBSR is an efficient mechanism that supports QoS for ad hoc networks.
38163613
Bayesian Learning for Image Retrieval Using Multiple Features
Image retrieval using multiple features often uses explicit weights that represent the importance of the features in their similarity metrics. In this paper, a novel retrieval method based on Bayesian Learning is presented. Instead of giving every feature a weight explicitly, the importance of a feature is regulated implicitly by learning a user's perception. Thus, the process of feature combination is adaptive and approximate to a user's perception. Experimental results demonstrate the significance of this method for improving the retrieval efficiency.
120181133
Face recognition based on discriminative manifold learning
In this paper, a discriminative manifold learning method for face recognition is proposed which achieved the discriminative embedding the high dimensional face data into a low dimensional hidden manifold. Unlike the recently proposed LLE, Isomap and Eigenmap algorithms, which are based on reconstruction purpose, our method uses the RCA algorithm to achieve nonlinear embedding and data discrimination at the same time. Also, the LLE and Isomap algorithms are crucially depends on the appropriateness of the neighborhood construction rule, in this paper, a CK-nearest neighborhood rule is proposed to achieve better neighborhood construction. Experimental results indicate the promising performance of the proposed method.