5771208
Image annotation by large-scale content-based image retrieval
Image annotation has been an active research topic in recent years due to its potentially large impact on both image understanding and Web image search. In this paper, we target at solving the automatic image annotation problem in a novel search and mining framework. Given an uncaptioned image, first in the search stage, we perform content-based image retrieval (CBIR) facilitated by high-dimensional indexing to find a set of visually similar images from a large-scale image database. The database consists of images crawled from the World Wide Web with rich annotations, e.g. titles and surrounding text. Then in the mining stage, a search result clustering technique is utilized to find most representative keywords from the annotations of the retrieved image subset. These keywords, after salience ranking, are finally used to annotate the uncaptioned image. Based on search technologies, this framework does not impose an explicit training stage, but efficiently leverages large-scale and well-annotated images, and is potentially capable of dealing with unlimited vocabulary. Based on 2.4 million real Web images, comprehensive evaluation of image annotation on Corel and U. Washington image databases show the effectiveness and efficiency of the proposed approach.
18118919
EnjoyPhoto: a vertical image search engine for enjoying high-quality photos
In this paper, we propose building a vertical image search engine called EnjoyPhoto that leverages rich metadata from various photo forum web sites to meet users' requirements for enjoying high-quality photos, which is virtually impossible in traditional image search engines. To solve the ranking problem when aggregating multiple photo forums, we propose a novel rank fusion algorithm that uses duplicate photos to normalize rating scores. To further improve user experiences in enjoying photos, we design an in-place image browsing interface, and compare it with several other interfaces in a user study. With rich metadata and rating information, more attractive user interfaces are enabled, including slideshow authoring and photo recommendations. We conducted experiments and user studies on a 2.5-million image database to evaluate the proposed rank fusion algorithm, investigate the rationale behind building a vertical image search engine, and study user interfaces and preferences for the purpose of enjoying high-quality photos. The experimental results demonstrate the effectiveness of the proposed ranking algorithm. The results also show that the 2.5-million high-quality image database in EnjoyPhoto performs comparably with Google's 1- billion image database for queries related to location, nature, and daily life categories. Finally, our results show that the in-place browsing interface-called Force-Transfer view-is much more convenient for users than traditional interfaces.
10396270
Temporal Shot Clustering Analysis for Video Concept Detection
The phenomenon that conceptually related shots appear together in videos is called temporal shot clustering. This phenomenon is a useful cue for video concept detection, which is one of basic steps in content-based video indexing and retrieval. We propose a method, called temporal shot clustering analysis, to improve results of video concept detection by exploiting the temporal shot clustering phenomenon. Two other methods are compared with temporal shot clustering analysis on the TRECVID 2003 dataset. Experiments showed that temporal shot clustering is of much benefit for video concept detection, and that temporal shot clustering method outperforms the other methods.
6035916
Ranking web objects from multiple communities
Vertical search is a promising direction as it leverages domain-specific knowledge and can provide more precise information for users. In this paper, we study the Web object-ranking problem, one of the key issues in building a vertical search engine. More specifically, we focus on this problem in cases when objects lack relationships between different Web communities, and take high-quality photo search as the test bed for this investigation. We proposed two score fusion methods that can automatically integrate as many Web communities (Web forums) with rating information as possible. The proposed fusion methods leverage the hidden links discovered by a duplicate photo detection algorithm, and aims at minimizing score differences of duplicate photos in different forums. Both intermediate results and user studies show the proposed fusion methods are practical and efficient solutions to Web object ranking in cases we have described. Though the experiments were conducted on high-quality photo ranking, the proposed algorithms are also applicable to other ranking problems, such as movie ranking and music ranking.
32640232
AP-Based Borda Voting Method for Feature Extraction in TRECVID-2004
We present a novel fusion method — AP-based Borda voting method (APBB)— for rankings. Due to its adaptive weighting scheme, APBB outperforms many traditional methods. Comparative experiments on TRECVID 2004 data were carried out and showed the robustness and effectiveness of this method.
9822806
Wavelet-based optical flow estimation
In this paper, a new algorithm for accurate optical flow estimation using discrete wavelet approximation is proposed. The proposed method takes advantages of the nature of wavelet theory, which can efficiently and accurately represent "things", to model optical flow vectors and image related functions. Each flow vector and image function are represented by linear combinations of wavelet basis functions. From such wavelet-based approximation, the leading coefficients of these basis functions carry the global information of the approximated "things". The proposed method can successfully convert the problem of minimizing a constraint function into that of solving a linear system of a quadratic and convex function of wavelet coefficients. Once all the corresponding coefficients are decided, the flow vectors can be determined accordingly. Experiments conducted on both synthetic and real image sequences show that our approach outperformed the existing methods in terms of accuracy.
335267
VLSI implementation of shape-adaptive discrete wavelet transform
In this paper, several VLSI architectures and implementations of Shape-Adaptive Discrete Wavelet Transform (SA-DWT) with odd symmetric biorthogonal filters are presented. The hardware implementation issues of SA-DWT algorithm are first addressed, and one lifting scheme together with some appropriate shape information processing units is introduced for the 1-D SA-DWT architectures. These architectures can efficiently perform 1-D length-adaptive DWT on continuous line segments and solve the corresponding boundary extension and subsampling problems without any overhead. In addition to 1-D architectures, two 2-D SA-DWT architectures are also proposed. One is the direct method, which uses the 1-D SA-DWT architectures as basis to extend to 2-D SA-DWT by direct row-column approach. The other is the line-based method, which is an efficient and feasible architecture that uses internal line buffers rather than external frame memory. These two 2-D SA-DWT architectures are both VLSI implemented by using cell-based chip design flow. The Daubechies (9,7) filter is used for the implementation by direct method, and the Daubechies (9,3) filter is used for the line-based implementation. The proposed architectures can be applied both in arbitrarily shaped visual objects coding such as MPEG-4 still texture coding and rectangular region image coding such as JPEG2000 still image coding.
21308144
EmoEars: An Emotion Recognition System for Mandarin Speech
In this paper, an emotion recognition system for mandarin speech is presented. Five basic human emotions including angry, fear, happy, neutral and sad are investigated. The recognizer is based on neural network with OCON and ACON architecture. Some novel feature selection methods are also added as optional tool to enhance the efficiency and classification accuracy. The system can train speaker dependent emotion speech model through online emotional utterance recording. Experiment results show that emotion can be recognized through neural network model, the best mean accuracy is 86.7%. In addition, the feature selection module is effective to reduce the compute load and increase the generalization ability of the recognizer.
27714693
Efficient Parallel Processing for K-Nearest-Neighbor Search in Spatial Databases
Even though the problem of k nearest neighbor (kNN) query is well-studied in serial environment, there is little prior work on parallel kNN search processing in parallel one. In this paper, we present the first Best-First based Parallel kNN (BFPkNN) query algorithm in a multi-disk setting, for efficient handling of kNN retrieval with arbitrary values of k by parallelization. The core of our method is to access more entries from multiple disks simultaneously and enable several effective pruning heuristics to discard non-qualifying entries. Extensive experiments with real and synthetic datasets confirm that BFPkNN significantly outperforms its competitors in both efficiency and scalability.
8697404
Audio streaming over Bluetooth: an adaptive ARQ timeout approach
Streaming audio has become a popular form of media on the Internet. As wireless personal area network architectures (e.g. Bluetooth) are now targeted to support multimedia traffic, streaming audio over these technologies give rise to interesting applications. But, the variable nature of the wireless medium will not lend itself easily to supporting audio streaming. We focus on Bluetooth and propose, an enhancement to the Bluetooth link layer ARQ mechanism to compensate for channel degradation and to better support audio streaming. Specifically, our scheme adoptively sets the ARQ timeout value based on current channel measurements. We show through testbed experiments that the adaptive ARQ improves the streaming quality significantly compared to the "vanilla" link layer of Bluetooth, especially in noisy environments. Our proposed approach is simple to implement and can actually be extended to the link layer of any wireless technology.