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Wearable equipment in recent years has been rapid development. But the hardware manufacturing complexity and the high cost is a real problem. This paper introduces a microprocessor cluster with both hardware design principle and related distributed software design methods. This cluster has the characteristics of low cost, high reliability, flexible hardware and software system structure, low power...
Hyperspectral image (HSI) is usually composed of hundreds of bands which contain very rich spatial and spectral information. However, the high-dimensional data may lead to the curse of dimensionality phenomenon when it is used for land use classification or other applications, making it difficult to be utilized effectively. In this paper, we developed a deep learning classification framework based...
Nowadays, the “semantic gap” problems have greatly limited development of image classification. The key to this problem is to get semantic information of the images. A semantic image feature extraction method is proposed in this paper, in which eye movement information is integrated. Firstly, the underlying visual features of images are extracted. Secondly, weighed feature vectors of images are constructed...
Autonomous UAV must rely on the navigation system to fly in the indoor environment. However, the traditional navigation system such as GPS cannot be used in the indoor environment. A method of Simultaneous Location and Mapping (SLAM) based on RGB-D cameras is used to solve this matter. We adopt the RGB-D SLAM algorithm to locate the camera and build the 3D map of the environment in this paper. The...
In this paper, an energy-efficient phonocardiogram (PCG) signal processor is proposed for wearable long-term cardiac monitoring. To achieve high energy efficiency, the proposed PCG processor employs pipelined and memory-less adaptive architecture to implement wavelet-domain statistic based real-time de-noising, heart sound peak detection, false peak filtering, S1/S2 peak identification and cardiac...
Multi-modal speaker recognition has received a lotof attention in recent years due to the growing security demands in real applications. In this paper, we present an efficient audio-visual speaker recognition method by fusing face and audio via the multi-modal correlated neural networks. Within our proposed approach, the facial features learned by convolutional neural networks are compatible with...
Cultural events are kinds of typical events closely related to history and nationality, which play an important role in cultural heritage through generations. However, automatically recognizing cultural events still remains a great challenge since it depends on understanding of complex image contents such as people, objects, and scene context. Therefore, it is intuitive to associate this task with...
Behavior recognition from large available motion capture data has received wide attention in the computer animation community and is growing increasingly important in recent years. In this paper, we present an efficient motion capture behavior recognition approach via neighborhood preserving dictionary learning. First, we normalize all the motion sequences in the database to make the motion to be...
Facial pose grouping plays an important role in the video face recognition. In this paper, we present an unsupervised facial pose grouping approach via Garbor subspace affinity and self-tuning spectral clustering. First, we utilize the local normalization method to reduce the impact of uneven illuminations, and then extract the discriminative appearance features via Gabor wavelet representation. Next,...
A compressed pornographic image recognition method is proposed by using incremental learning. For describing pornographic image, visual words are created from low-resolution (LR) image reconstructed from the compressed stream of the pornographic image. Covering algorithm is utilized to train and recognize the visual words in order to build the initial classification model of pornographic image. At...
In this paper, we address an exemplar-based hidden markov model (HMM) that represents the lip motion activity using visual cues for lipreading. The discriminative visual features including the geometric shape parameters and contour-constrained spatial histogram are selected for representing each lip frame. Then, a set of exemplars associated with the HMM is learned jointly to serve as a typical representation...
With the rapid development of social media, research about its application and organization has attracted considerable attention. Many social media sharing websites allow users to tag the uploaded images with tags. However, the tags are usually uncontrolled, ambiguous, and overly personalized. One of the most challenging issues is how to match the textual tags with the visual image to rank tags accurately...
For the network environment with the limited transmission capacity, a multi-nodes image retrieval method based on visual words is proposed. Firstly, the visual words of query image are built by using the K-means clustering method after the color features and SIFT features of query image are extracted. Then the visual-words histogram of the query image is carried by the mobile Agent. The image similarity...
Face recognition is one important task in Nomad Biometric Authentication (NOBA) project. However, as many other face databases, it will easily produce the Small Sample Size (SSS) problem in some applications with NOBA data. Thus this paper uses the Compressed Sensing (CS) algorithm to solve the SSS problem in NOBA face database. Some experiments can prove the feasibility and validity of this solution.
This paper investigates the problem of acquiring planar object maps of indoor household environments in particular kitchens. The objects modeled in these maps include tables, walls and ceilings. Our segmentation approach is based on 3D point cloud data representations. In order to solve the segmentation problem in complicated environment, a variable model is used in this paper. It is applied in 3D...
This paper presents a real-time object segmentation approach for visual object detection in dynamic scenes. This object segmentation approach is based on a novel general object feature which is defined subtly combining multiple low-level features and the uniqueness of the target object. Then the object segmentation approach is applied to detect vehicle and lane marking in dynamic scenes. Experiment...
This paper presents a real-time long-range lane detection and tracking approach to meet the requirements of the high-speed intelligent vehicles running on highway roads. Based on a linear-parabolic two-lane highway road model and a novel strong lane marking feature named Lane Marking Segmentation, the maximal lane detection distance of this approach is up to 120 meters. Then the lane lines are selected...
This paper presents a vision-based real-time vehicle detection approach. Combining segmenting the specific shadow area underneath the vehicle and using SVM-based classifier, the proposed approach is accurate and efficient for intelLigent vehicle. Experiment results with test dataset from real traffic scenes on freeways and urban roads are presented to illustrate the performance of this approach.
Speed limit signs play a vital role in traffic control, as an important means of controlling the vehicle speed. Therefore, achieving the correct recognition of speed limit sign is particularly critical in the road traffic sign recognition system research. In order to probe into accuracy problems and speed problems of the urban road speed limit detection, on the basis of color-geometric features of...
In this paper, a new method that incorporates the spatial information to localize prostate cancer with magnetic resonance imaging (MRI) is proposed. Most automated methods for tumor localization require manual peripheral zone extraction from the prostate gland, and it is a tedious and time-consuming job with considerable inter-observer variability. In order to conquer this difficulty, we propose to...
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