In the field of object detection, it is hoped that the model trained in the domain with a lot of labels can be applied to other domains without labels, but different domain distributions are always different to each other, such difference will result in a sharp decline of model performance in domain transfer. To improve the model performance of object detection in domain transfer, the domain transfer was addressed on two levels, including the global-level transfer and the local-level transfer, which were corresponding to different feature alignment methods, that is, the global-level adopted selective alignment and the local-level adopted full alignment. The proposed domain transfer framework was constructed based on Single Shot MultiBox Detector (SSD) model and was disposed of two domain adaptors corresponding to global and local level respectively for the purpose of alleviating the domain difference. The specific training was implemented by the adversarial network algorithm, and the consistency regularization was used to further improve the domain transfer performance of the model. The effectiveness of the proposed domain transfer model was verified by many experiments. Experimental results show that on various datasets, the proposed model outperforms the existing common domain transfer models such as Domain Adaptation-Faster Region-based Convolutional Neural Network(DA-FRCNN), Adversarial Discriminative Domain Adaptation (ADDA), Dynamic Adversarial Adaptation Network (DAAN) by 5%-10% in term of mean Average Precision (mAP).

A new Tone Mapping (TM) algorithm based on multi-scale decomposition was proposed to solve a High Dynamic Range (HDR) image displayed on an ordinary display device. The algorithm decomposed a HDR image into multiple scales using a Local Edge-Preserving (LEP) filter to smooth the details of the image effectively, while still retaining the salient edges. Then a dynamic range compression function with parameters was proposed according to the characteristics of the decomposed layers and the request of compression. By changing the parameters, the coarse scale layer was compressed and the fine scale layer was boosted, which resulted in compressing the dynamic range of the image and boosting the details. Finally, by restructuring the image and restoring the color, the image after mapping had a good visual quality. The experimental results demonstrate that the proposed method is better than the algorithm proposed by Gu et al.(GU B, LI W J, ZHU M Y, et al. Local edge-preserving multiscale decomposition for high dynamic range image tone mapping ［J］. IEEE Transactions on Image Processing, 2013, 22(1): 70-79) and Yeganeh et al. (YEGANEH H, WANG Z. Objective quality assessment of tone-mapped images ［J］. IEEE Transactions on Image Processing, 2013, 22(2): 657-667) in naturalness, structural fidelity and quality assessment; moreover, it avoids the halo artifacts which is a common problem existing in the local tone mapping algorithms. The algorithm can be used for the tone mapping of the HDR image.

Network bandwidth is one of the bottlenecks of the Web cameras performance. So we proposed an approach of Web camera based on MPEG4. This paper introduces the design of Web cameras hardware and software. With PNX1301 chip, an applicable Web camera was implemented. Then the design and implementation of the PCI arbiter was given in detail.