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Vision-based Simultaneous Localisation and Mapping (Visual SLAM) is a new hot topic in intelligent robotic applications. A new method for the implementation of a visual SLAM system with monocular vision is proposed in this paper. The general framework of our system is first displayed, and then all the main sub-processes are described step by step. In our design we use the ORB feature to represent...
Handheld devices with “glasses-free” autostereoscopic displays present a new opportunity for 3D video communications. 3D can enhance realism and enrich the user experience, yet it must be employed without visual discomfort. A simple shift-convergence disparity remapping technique can align a user's face throughout a 3D video call, eliminating uncomfortable crossed disparities. However, this can produce...
Chinese Calligraphy is one traditional form of Chinese art and was listed in UNESCO's World Culture Heritage in 2009. Traditional method to learn calligraphy is inconvenient as it needs paper, Chinese ink and brush. And learner's especially for foreigners feel difficulty for stroke order of Chinese character is complex and even same character has different stroke orders with different font style....
The co-occurrence features are the composition of base features that have more discriminative power than individual base features. Although they show promising performance in visual recognition applications such as object and scene recognition, the discovery of discriminative co-occurrence features is usually a computational demanding task. Unlike previous feature mining methods that fix the order...
In networked video stream mining systems, real-time video contents are captured remotely and, subsequently, encoded and transmitted over bandwidth-constrained networks for classification at the receiver. One key task at the encoder is to adapt its compression on the fly based on time-varying network bandwidth and video characteristics — while attaining low delay and high classification accuracy. In...
We propose a novel hierarchical sparse coding algorithm with spatial pooling and multi-feature fusion, to construct the low-level visual primitives, e.g., local image patches or regions, into high-level visual phrases, e.g., image patterns. In the first layer we learn the sparse codes for the visual primitives and then pass them into the second layer by spatial pooling and multi-feature fusion. In...
The Deformable Part Model has shown high accuracy in tackling certain occlusion or deformations of objects such as cars and bikes. However, as for human category characterized by a larger number of articulated parts and more significant appearance variations, its performance gain is not so remarkable. To address this issue, we propose an MPLBoost-based mixture model which splits data into coherent...
Exemplar-based clustering has drawn much attention in recent years as it produces state-of-the-art results on many practical clustering problems. However, spatial information is missed in the exemplar-based clustering methods, resulting in difficulties in some applications, for example in the image segmentation problem. In this paper, we investigate the issue of integrating spatial information into...
Unsupervised extraction of focused regions from images with low depth-of-field (DOF) is a problem without an efficient solution yet. In this paper, we propose an efficient unsupervised segmentation solution for this problem. The proposed approach which is based on ensemble clustering and graph-cut modeling aims to extract meaningful focused regions from a given image at two stages. In the first stage,...
In this paper, a Dynamic Structure Preserving Map (DSPM) is proposed to effectively recognize human actions in video sequences. Inspired by the latest feature learning methods, we modified and improved the adaptive learning procedure in self-organizing map (SOM) to capture dynamics of best matching neurons through Markov random walk. The DSPM can learn implicit spatial-temporal correlations from sequential...
An effective and efficient image contour detector is highly desired due to its wide applications in computer vision and multimedia retrieval. However, the state-of-the-art image contour detection algorithms are very computationally intensive, and thus impractical for web-scale applications. In this work, we study the relationship between edge detection and contour detection, based on which an edge-based...
Calculation of the number of cameras required to capture the scene is an essential problem in a practical light field based free viewpoint video (FVV) system. Existing methods calculate the Nyquist rate by assuming a band-limited signal and perfect reconstruction of an arbitrary view using linear interpolation, which often results in an impractically high number of cameras. This paper proposes a new...
A region-based frame rate up-conversion (FRUC) algorithm based on higher-order global and local motion is proposed in this paper. First, perspective global motion parameters are estimated so that backgrounds of neighboring frames can be aligned. Then, the foreground is separated from the background using structural similarity, and iteratively decomposed into regions with homogeneous motion that fit...
In a free viewpoint video system, the scene is captured by a number of cameras and it would be desirable to optimize the configuration of cameras, such as their location or orientation, to improve the rendering quality. This paper introduces a mathematical representation of the multi-camera geometry, called the correspondence field (CF), which can be used to quantify the suitability of a camera configuration...
The behaviour, goals, and intentions of users while searching for images in large scale online collections are not well understood, with image search log analysis providing limited insights, in part because they tend only to have access to user search and result click information. In this paper we study user search behaviour in a large photo-sharing platform, analyzing all user actions during search...
Detecting topics from Web data attracts increasing attention in recent years. Most previous works on topic detection mainly focus on the data from single medium, however, the rich and complementary information carried by multiple media can be used to effectively enhance the topic detection performance. In this paper, we propose a flexible data fusion framework to detect topics that simultaneously...
This paper proposes a novel approach for partial blur detection and segmentation. The local blur kernels of image blocks are firstly estimated and then a reblurring technique is used to measure relative blur degrees of the local blur kernels. The output of reblurring is a metric to classify blurred and non-blurred image blocks. Furthermore, block-based and pixel-based techniques are incorporated for...
In this paper we propose novel approaches for robust blur removal and image reconstruction considering uncertainty in the blur kernel. The stochastic minimization approach models the kernel uncertainty as a stochastic spatial random process, while the worst case reconstruction is a robust minimax scheme which minimizes the maximum image distortion over a set of uncertainty blur kernels. The worst...
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