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Sentiment analysis from large-scale networked data attracts increasing attention in recent years. Most previous works on sentiment prediction mainly focus on text or image data. However, voice is the most natural and direct way to express people's sentiments in real-time. With the rapid development of smart phone voice dialogue applications (e.g., Siri and Sogou Voice Assistant), the large-scale networked...
Privacy protection is of increasing importance in this era of information explosion. This paper introduces an information security display system based on the idea of Spatial Psycho-visual Modulation (SPVM). With the rapid advance of modern manufacturing techniques, display devices now support very high pixel density (e.g. the retina display of Apple). Meanwhile the human visual system (HVS) cannot...
Eye localization is a key step in many face analysis related applications. In this paper, we present a novel eye localization method based on a group of trained filters called correlation filter bank (CFB). We formulate the eye localization problem as an optimization problem with a well-defined cost function based on CFB. The CFB is trained with an EM-like adaptive clustering approach. The trained...
Although total variation minimization technique is being widely used in compressive sensing recovery, it still suffers from the so called staircase artifact which is caused by losing fine details of image. As a solution for the problem, in this paper, we propose an edge-preserving weighting scheme utilizing nonlocal structure and histogram of natural image in the gradient domain. Experimental results...
A novel scheme for single-rate compression of material and texture attributes for triangular meshes is proposed in this work. For the material coding, it proposes a novel approach based on breadth-first surface traversal, exploiting the local coherence of the material attributes among neighboring facets; for the texture coordinate coding, it proposes a similar-triangle-based prediction method, exploiting...
We introduce and investigate a novel problem of image recommendation for web search engine users. Modern web search engines have become a critical assistant for people's daily life. Through interacting with web search engines, users exhibit personalized information needs in various aspects. While this information is critical to improve user experience, it is mostly used only in the web search domain...
Recently, consumer depth cameras have gained significant popularity due to their affordable cost. However, the limited resolution and quality of the depth map generated by these cameras are still problems for several applications. In this paper, we propose a new algorithm for depth image super resolution using a single depth image as input. We reconstruct the corresponding high resolution depth map...
This paper develops a novel learning-based method for detecting stereo saliency in stereopair images. The disparity maps computed from stereopair images provide an additional depth cue for stereo saliency detection. To the best of our knowledge, our approach is the first one to simultaneously detect the stereo saliency of both left and right images using support vector machine (SVM). In our work,...
Sparse representation has been widely applied to some generative tracking methods. However, these methods do not consider the correlation between sparse representation coefficients in the time domain. In this paper, we propose a novel incremental subspace dynamic sparse tracking (ISDST) model with the error term of Gaussian-Laplacian distribution, which fully considers the correlation of object representations...
The packet loss and handover tend to occur often in burst in heterogeneous wireless network. The Sender-based transport control mechanisms make current SCTP cannot provide an expected adaptive transmission rate adjustment and recovery strategy to ensure the users' quality of experience for multimedia streaming service due to the abrupt and frequent transmission rate fluctuation. Moreover, current...
Compressed Sensing (CS) has drawn quite an amount of attention as novel digital signal sampling theory in recent years when the signal is sparse in some domain. However, signal reconstruction from undersampled data has always been challenging due to its implicit ill-posed nature. This paper proposes an image compressed sensing reconstruction algorithm for image CS application, which consists of iteratively...
This paper proposes a fast mode decision algorithm for 3D High Efficiency Video Coding (3D-HEVC) depth intra coding. In the current 3D-HEVC design, it is observed that for most of the cases, full Rate-Distortion (RD) cost search of Bi-partition mode could be skipped since most coding units (CUs) of depth map are very flat or smooth while Bi-partition modes are designed for CUs with edge or sharp transition...
Constructing effective representations is a critical but challenging problem in multimedia understanding. The traditional handcraft features often rely on domain knowledge, limiting the performances of exiting methods. This paper discusses a novel computational architecture for general image feature mining, which assembles the primitive filters (i.e. Gabor wavelets) into compositional features in...
As the increasing popularity of superpixel-based applications, measuring superpixel-level similarity becomes an important and commonly required problem. In this paper, we propose a general bag of squares (BoS) model for such particular purpose. Compared to existing methods, our approach provides a full scheme to both invariantly represent superpixels and accurately measure their pairwise similarities...
Detecting the beginning and end of a specific gesture from an infinite trajectory gesture sequence has gained considerable interests in the past several years. Traditional begin-end dynamic time warping approach for gesture recognition could provide multiple different gesture labels for one trajectory segment. This paper presents a Windowed Dynamic Time Warping (WDTW) approach for 3D continuous hand...
Given the proliferation of geo-tagged images, geo-aware image classification is an emerging topic. To derive a better image representation, tag features which represents an image as a histogram of tags are recently introduced. However, it is unclear whether geo tags can improve the tag features. To resolve the uncertainty, this paper studies geo-aware tag features. Our work is based on previous work...
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