A wavelength-division-multiplexing (WDM) visible light communiction (VLC) system employing red and green laser pointer lasers (LPLs) with directly modulating data signals is proposed and experimentally demonstrated. With the assistance of preamplifier and adaptive filter at the receiving sites, low bit error rate (BER) at 10 m/500 Mbps operation is obtained for each wavelength. The use of preamplifier and adaptive filter offer significant improvements for free-space transmission performance. Improved performance of BER of <10(-9), as well as better and clear eye diagram were achieved in our proposed WDM VLC systems. LPL features create a new category of good performance with high-speed data rate, long transmission length (>5m), as well as easy handling and installation. This proposed WDM VLC system reveals a prominent one to present its advancement in simplicity and convenience to be installed.

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By controlling the output coupling ratio, we demonstrate a novel wavelength-tunable L-band Erbium-doped fiber laser (EDFL) with a maximum tuning range up to 58 nm (from 1567 to 1625 nm) by controlling its output coupling ratio between 1% and 99%. The L-band EDFL is configured by using a bi-directionally dual-wavelength pumped EDFA in close-loop with an output coupler of tunable coupling ratio and an air-gap inserted FC/PC connector pair. Such an EDFL exhibits a quantum efficiency of 42% and an ultra-high power conversion efficiency of 37% under optimized pumping scheme, providing the small-signal gain and output power of ~34 dB and 91 mW, respectively. Low variation of <1.2 dB on channel power, power fluctuation of 0.04% and a narrow linewidth of 0.03 nm are obtained.

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In this paper, we propose a visual tracking approach based on 'bag of features' (BoF) algorithm. First we use incremental PCA visual tracking (IVT) in the first few frames and collect image patches randomly sampled within the tracked object region in each frame for constructing the codebook; the tracked object then can be converted to a bag. Second we construct two codebooks using color (RGB) features and local binary pattern (LBP) features instead of only one codebook in traditional BoF, thereby extracting more informative details. We also devise an updating mechanism to deal with pose and appearance changes of objects. In the tracking process, a constant number of candidates are generated by sampling technique in each frame. Image patches are then randomly sampled and candidates are represented as bags by codebooks. Thus, we can compute patch similarity of a candidate with the codewords and bag similarity with trained bags. The actual object is then located by finding the maximal combined similarity of patches and bags. Experiments demonstrate that our approach is robust in handling occlusion, scaling and rotation.