28547446
Low-Complex Equalization for Single Carrier Systems Employing Cyclic Prefix over Time-Variant Channels
A simplified equalization method based on the band structure of the frequency domain channel matrix is proposed for the single carrier systems employing cyclic prefix (SC-CP) over time-varying wireless channels. Using both theoretical analysis and computer simulation, it is shown that the complexity of this method is proportional to the number of symbols in one SC-CP block and is less than that of traditional block equalization methods. We also show that they have similar performance.
7144886
Khatri-Rao Unitary Space-Time Modulation
Based on the Khatri-Rao matrix product, we propose a novel unitary space-time modulation design called KR-USTM in this paper. Different from existing USTM schemes, such as the systematic approach and space-time frequency-shift keying (ST-FSK), KR-USTM does not require any computer search and can be applied to any number of transmit antennas. Moreover, the special structure of KR-USTM also makes it a high-rate scheme and achieve full antenna diversity as well as lower decoding complexity. Simulation results show that the proposed KR-USTM constellation achieves error performance comparable to existing USTM designs at low rates, while it outperforms them at high rates.
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.
26132055
Car Plate Localization Using Pulse Coupled Neural Network in Complicated Environment
Car plate recognition is an important problem in many traffic related applications. In this paper, we focus on car plate localization-the first step of car plate recognition. We propose a hybrid method based on Pulse Coupled Neural Network (PCNN) and wavelet analysis. First of all, we use PCNN to enhance the image. Then, regions of interest (ROIs) will be get through wavelet analysis. After that, PCNN enhancement is applied again in ROIs, followed by a training and classification process for final labelling ROIs as car plate regions or not. Experiment results show that the precision can get 96%, which is higher than other localization methods on the same image database.
34620301
Video Local Pattern based Image Matching for Visual Mapping
Image matching plays an important role in visual mapping, a critical task of vision based mobile robot navigation. Based on the observation that the visual content in these video sequences generally changes in a slow and continuous mode, a concept of "video local pattern" is proposed to model each video frame, which is defined as a set of frames that are visually-similar and temporally-adjacent to that frame. Instead of manually labelling, a tracking based method is developed to automatically detect the local pattern for each frame. A model is then estimated from a local pattern, and the matching of images is performed by comparing these models. Experimental results demonstrated its improvement over that comparing individual frames
46712099
Side Information Inserted Pilot Tone Transmission for PAPR Reduction in OFDM
In order to reduce the peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) signals over fading channels, the selected mapping (SLM) scheme and channel estimation technique can be used. Because of the side information of SLM, however, the data rate decreases in the conventional transmission method. In this letter, to overcome this impairment, we propose a technique which transmits side information by using pilot tones. Numerical analysis and computer simulations show that this method can maintain the PAPR reduction ability of SLM while improving error performance.
7727851
Facial Features Location by Analytic Boosted Cascade Detector
We describe a novel technique called Analytic Boosted Cascade Detector (ABCD) to automatically locate features on the human face. ABCD extends the original Boosted Cascade Detector (BCD) in three ways: (i) a probabilistic model is included to connect the classifier responses with the facial features; (ii) a features location method based on the probabilistic model is formulated; (iii) a selection criterion for face candidates is presented. The new technique melts face detection and facial features location into a unified process. It outperforms Average Positions (AVG) and Boosted Classifiers + best response (BestHit). It also shows great speed superior to the methods based on nonlinear optimization, e.g. AAM and SOS.