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检索条件"任意字段=Conference on Visual Communications and Image Processing 2007"

共 4985 条记录，以下是171-180 订阅

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The Enhancement of Underexposed images with Blurred Reflectance

The Enhancement of Underexposed Images with Blurred Reflecta...

引用

IEEE International conference on visual communications and image processing (VCIP)

作者： Zhou, Jinchao Wan, Renjie Li, Haoliang Kot, Alex C. Beihang Univ Sch Comp Sci & Engn Beijing Peoples R China Nanyang Technol Univ Sch Elect & Elect Engn Singapore Singapore

ISBN: (纸本)9781728180687

The images captured in the low-light conditions always suffer from low visibility. Enhancing the visibility of the low-light image is of broad application to various computer vision tasks. Based on the classical Retinex model, previous methods assume the reflectance components as a well-exposed image. In this paper, we introduce the blurring distortion into the Retinex model to cover more general and challenging scenarios. We further propose a two-stage framework to extract the reflectance images and remove the blurring distortion separately. Specifically, we optimize the whole network by embedding a mechanism robust to the pixel misalignment in the training dataset. The experimental results show that our proposed method achieves promising results.

关键词： Low-light image blur illumination reflectance

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Learning in Compressed Domain for Faster Machine Vision Tasks

Learning in Compressed Domain for Faster Machine Vision Task...

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IEEE International conference on visual communications and image processing (VCIP) - visual communications in the Era of AI and Limited Resources

作者： Liu, Jinming Sun, Heming Katto, Jiro Waseda Univ Dept Comp Sci & Commun Engn Tokyo Japan Waseda Univ Waseda Res Inst Sci & Engn Tokyo Japan JST PRESTO 4-1-8 Honcho Kawaguchi Saitama Japan

ISBN: (纸本)9781728185514

Learned image compression (LIC) has illustrated good ability for reconstruction quality driven tasks (e.g. PSNR, MS-SSIM) and machine vision tasks such as image understanding. However, most LIC frameworks are based on pixel domain, which requires the decoding process. In this paper, we develop a learned compressed domain framework for machine vision tasks. 1) By sending the compressed latent representation directly to the task network, the decoding computation can be eliminated to reduce the complexity. 2) By sorting the latent channels by entropy, only selective channels will be transmitted to the task network, which can reduce the bitrate. As a result, compared with the traditional pixel domain methods, we can reduce about 1/3 multiply-add operations (MACS) and 1/5 inference time while keeping the same accuracy. Moreover, proposed channel selection can contribute to at most 6.8% bitrate saving.

关键词： compressed domain image compression face alignment video coding for machine

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visual Attention Based image Zero Watermark Scheme With Ensemble Similarity

Visual Attention Based Image Zero Watermark Scheme With Ense...

引用

International conference on Wireless communications and Signal processing (WCSP)

作者： Shi, Jie Yan, Qin Shi, Huijuan Wang, Yapeng Hohai Univ Coll Comp & Informat Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781479903085

Most existing digital image watermarking schemes tend to have the inherent conflicts between imperceptibility and robustness because watermarks are embedded by parameter modification. image watermark techniques resolve this dilemma by extracting invariant features from the image as "embedded" watermark. In this paper we propose an image zero watermark scheme based on visual attention regions of images. In the proposed scheme visual attention model carefully selects top-N salient areas, where a set of selected Scale Invariant Feature transform (SIFT) descriptors are extracted as a watermark. The distance of each pair of SIFT descriptors from the reference and test images are calculated by Kullback-Leibler (KL) divergence after mapping into the high dimensional space respectively. The final distance of two sets of SIFT descriptor are determined by ensemble similarity. The experimental results indicate that the proposed scheme outperforms image zero watermark scheme based on color and edge histograms (CEH) and is robust to attacks of geometric distortion, contrast/luminance distortion and JPEG compression.

关键词： image watermark visual attention ensemble similarity SIFT authentication

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Region-based hidden Markov models for image categorization and retrieval

Region-based hidden Markov models for image categorization a...

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conference on visual communications and image processing 2007

作者： Li, Fei Dai, Qionghai Xu, Wenli Tsinghua Univ Dept Automat Beijing 100084 Peoples R China

ISBN: (纸本)9780819466211

Hidden Markov models (HMMs) have been widely used in various fields, including image categorization and retrieval. Most of the existing methods train HMMs by low-level features of image blocks;however, the block-based features can not reflect high-level semantic concepts well. This paper proposes a new method to train HMMs by region-based features, which can be obtained after image segmentation. Our work can be characterized by two key properties: (1) Region-based HMM is adopted to achieve better categorization performance, for the region-based features accord with the human perception better. (2) Multi-layer semantic representation (MSR) is introduced to couple with region-based HMM in a long-term relevance feedback framework for image retrieval. The experimental results demonstrate the effectiveness of our proposal in both aspects of categorization and retrieval.

关键词： Hidden Markov model (HMM) multi-layer semantic representation (MSR) image categorization image retrieval

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Learn A Compression for Objection Detection - VAE with a Bridge

Learn A Compression for Objection Detection - VAE with a Bri...

引用

IEEE International conference on visual communications and image processing (VCIP) - visual communications in the Era of AI and Limited Resources

作者： Mei, Yixin Li, Fan Li, Li Li, Zhu Xi An Jiao Tong Univ Sch Informat & Commun Engn Xian Peoples R China Univ Sci & Technol China Dept Elect Engn & Informat Sci Hefei Peoples R China Univ Missouri Dept Comp Sci & Elect Engn Kansas City MO 64110 USA

ISBN: (纸本)9781728185514

Recent advances in sensor technology and wide deployment of visual sensors lead to a new application whereas compression of images are not mainly for pixel recovery for human consumption, instead it is for communication to cloud side machine vision tasks like classification, identification, detection and tracking. This opens up new research dimensions for a learning based compression that directly optimizes loss function in vision tasks, and therefore achieves better compression performance vis-a-vis the pixel recovery and then performing vision tasks computing. In this work, we developed a learning based compression scheme that learns a compact feature representation and appropriate bitstreams for the task of visual object detection. Variational Auto-Encoder (VAE) framework is adopted for learning a compact representation, while a bridge network is trained to drive the detection loss function. Simulation results demonstrate that this approach is achieving a new state-of-the-art in task driven compression efficiency, compared with pixel recovery approaches, including both learning based and handcrafted solutions.

关键词： image coding for machine object detection learning-based image compression

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A 2-D gel electrophoresis DNA image analysis algorithm with automatic thresholding

A 2-D gel electrophoresis DNA image analysis algorithm with ...

引用

conference on visual communications and image processing 2007

作者： Kaabouch, Naima Schultz, Richard R. Univ North Dakota Dept Elect Engn Grand Forks ND 58201 USA

ISBN: (纸本)9780819466211

Polymerase chain reaction (PCR) and gel electrophoresis are two widely used techniques for genetic studies that require the bench scientist to perform many tedious manual steps. Advances in automation are making these techniques more accessible, but detection and image analysis still remain labor-intensive. Although several commercial software packages are now available, DNA image analysis still requires some intervention by the user, and thus a certain level of image processing expertise. To allow researchers to speed up their analyses and obtain more repeatable results, we present a fully automated image analysis system for DNA or protein studies with high accuracy. The proposed system is based mainly on four steps: automatic thresholding, shifting, filtering, and processing. The automatic thresholding that is used to equalize the gray values of the gel electrophoreses image background is one of the key and novel operations in this algorithm. An enhancement is also used to improve poor quality images that have faint DNA bands. Experimental results show that the proposed method eliminates defects due to noise for good and average quality gel electrophoresis images, while it also improves the appearance of poor quality images.

关键词： electrophoresis gel image analysis DNA bands thresholding

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AUTOMATIC ANNOTATION OF DIGITAL imageS USING COLOUR STRUCTURE AND EDGE DIRECTION

AUTOMATIC ANNOTATION OF DIGITAL IMAGES USING COLOUR STRUCTUR...

引用

IEEE International conference on Signal processing and communications

作者： Shao, Wenbin Naghdy, Golshah Phung, Son Lam Univ Wollongong Sch Elect Comp & Telecommun Engn Wollongong NSW 2522 Australia

ISBN: (纸本)9781424412358

The focus of this paper is on automatic annotation for semantic image retrieval. This work is aimed at identifying visual descriptors that are most relevant, effective and suitable for semantic annotation tasks. We propose an image annotation system based on support vector machines and a combination of descriptors that includes a gradient direction histogram and several MPEG-7 visual descriptors. The system is tested on a large database of 7200 cityscape and landscape images. The results indicate that when descriptors are used individually, the proposed gradient direction histogram performs best. However, when descriptors are combined, the accuracy is improved. The presented results confirm that combining the gradient direction histogram and colour structure produces the best results.

关键词： image classification SVMs MPEG-7 gradient direction histogram

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Text-to-image Generation via Semi-Supervised Training

Text-to-Image Generation via Semi-Supervised Training

引用

IEEE International conference on visual communications and image processing (VCIP)

作者： Ji, Zhongyi Wang, Wenmin Chen, Baoyang Han, Xiao Peking Univ Sch Elect & Comp Engn Shenzhen Grad Sch Shenzhen Peoples R China Macau Univ Sci & Technol Intemat Inst Next Generat Internet Macau Peoples R China

ISBN: (纸本)9781728180687

Synthesizing images from text is an important problem and has various applications. Most of the existing studies of text-to-image generation utilize supervised methods and rely on a fully-labeled dataset, but detailed and accurate descriptions of images are onerous to obtain. In this paper, we introduce a simple but effective semi-supervised approach that considers the feature of unlabeled images as " Pseudo Text Feature". Therefore, the unlabeled data can participate in the following training process. To achieve this, we design a Modality-invariant Semanticconsistent Module which aims to make the image feature and the text feature indistinguishable and maintain their semantic information. Extensive qualitative and quantitative experiments on MNIST and Oxford-102 flower datasets demonstrate the effectiveness of our semi-supervised method in comparison to supervised ones. We also show that the proposed method can be easily plugged into other visual generation models such as image translation and performs well.

关键词： image Synthesis Text-to-image Generation Semi-Supervised Learning Pseudo Feature

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An 81.6 GOPS object recognition processor based on NoC and visual image processing memory 29

An 81.6 GOPS object recognition processor based on NoC and v...

引用

IEEE Custom Integrated Circuits conference

作者： Kim, Donghyun Kim, Kwanho Kim, Joo-Young Lee, Seungjin Yoo, Hoi-Jun Korea Adv Inst Sci & Technol Dept Elect Engn & Comp Sci Semicond Syst Lab Taejon 305701 South Korea

ISBN: (纸本)9781424407866

An 81.6 GOPS object recognition processor is developed by using NoC and visual image processing (VIP) memory. SIFT (Scale Invariant Feature Transform) object recognition requires huge computing power and data transactions among tasks. The chip integrates 310 SIMD PEs for data/task level parallelism while the NoC facilitates inter-PE communications. The VIP memory searches local maximum pixel inside a 3x3 window in a single cycle providing 65.6 GOPS. The proposed processor achieves 15.9fps SIFT feature extraction at 200 MHz.

关键词： GOPS object recognition computational power PROCESSOR image processing

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Deep Motion Flow Aided Face Video De-identification

Deep Motion Flow Aided Face Video De-identification

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IEEE International conference on visual communications and image processing (VCIP) - visual communications in the Era of AI and Limited Resources

作者： Wen, Yunqian Liu, Bo Xie, Rong Cao, Jingyi Song, Li Shanghai Jiao Tong Univ Inst Image Commun & Network Engn Shanghai Peoples R China Univ Technol Sydney Sch Comp Sci Sydney NSW Australia

ISBN: (纸本)9781728185514

Advances in cameras and web technology have made it easy to capture and share large amounts of face videos over to an unknown audience with uncontrollable purposes. These raise increasing concerns about unwanted identity-relevant computer vision devices invading the characters's privacy. Previous de-identification methods rely on designing novel neural networks and processing face videos frame by frame, which ignore the data feature in redundancy and continuity. Besides, these techniques are incapable of well-balancing privacy and utility, and per-frame evaluation is easy to cause flicker. In this paper, we present deep motion flow, which can create remarkable de-identified face videos with a good privacy-utility tradeoff. It calculates the relative dense motion flow between every two adjacent original frames and runs the high quality image anonymization only on the first frame. The de-identified video will be obtained based on the anonymous first frame via the relative dense motion flow. Extensive experiments demonstrate the effectiveness of our proposed de-identification method.

关键词： video de-identification video anonymization privacy protection privacy-utility tradeoff

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