三维重建中深度图像配准方法研究

三维重建是计算机视觉的主要目的,也是计算机图形学领域的研究热点。通过两两配准和多视角配准的深度介绍和举例说明,系统介绍了深度图像配准方法。通过这些方法可以大大简化三维物体的识别和定位等问题,开辟了机器视觉的一个新途径。     

Advances in matrix manifolds for computer vision

The attention paid to matrix manifolds has grown considerably in the computer vision community in recent years. There are a wide range of important applications including face recognition, action recognition, clustering, visual tracking, and motion grouping and segmentation. The increased popularity of matrix manifolds is due partly to the need to characterize image features in non-Euclidean spaces. Matrix manifolds provide rigorous formulations allowing patterns to be naturally expressed and classified in a particular parameter space. This paper gives an overview of common matrix manifolds employed in computer vision and presents a summary of related applications. Researchers in computer vision should find this survey beneficial due to the overview of matrix manifolds, the discussion as well as the collective references.     

一种基于混合分类器的人眼定位方法

人眼定位是计算机视觉的关键技术,它在视频监控、人脸识别系统以及新一代的人机交互技术等领域有着实际的应用价值。采用先对图像建立肤色模型,然后运用支持向量机的训练结果来构成分类器,在人脸区域定位人眼。     

采用视觉注册的户外增强现实技术的研究

目前户外增强现实技术多采用硬件跟踪的注册方法解决浏览展示方面的问题。为了户外规划设计方面的应用需求,需要使用更加便于交互的基于视觉的注册方法。利用计算机视觉的方法并辅助于测距仪器便可以计算出视觉注册中必备的标定点空间坐标,从而使得增强现实技术可以应用到图像级的户外规划设计领域,并通过将摄像机坐标系和世界坐标系重合设置简化了注册过程。这些工作将有助于用户在景区规划设计等领域做出更好的决策。     

Scene text detection with fully convolutional neural networks

Multimedia Tools and Applications - Text detection in scene image has become a hot topic in computer vision and artificial intelligence research, due to its wide range of applications and...     

Human action recognition: a framework of statistical weighted segmentation and rank correlation-based selection

Pattern Analysis and Applications - Human action recognition from a video sequence has received much attention lately in the field of computer vision due to its range of applications in...     

Computer Vision Systems for Industrial Inspection and Assembly

Custom-designed computer vision systems are being applied to specific manufacturing tasks. Current development may lead to general-purpose systems for a broad range of industrial applications.     

A nonlocal gradient concentration method for image smoothing

Computational Visual Media - It is challenging to consistently smooth natural images, yet smoothing results determine the quality of a broad range of applications in computer vision. To achieve...     

Deep Learning Based Single Image Super-resolution: A Survey

Machine Intelligence Research - Single image super-resolution has attracted increasing attention and has a wide range of applications in satellite imaging, medical imaging, computer vision,...     

Semantic network array processor and its applications to image understanding

The problems in computer vision range from edge detection and segmentation at the lowest level to the problem of cognition at the highest level. This correspondence describes the organization and operation of a semantic network array processor (SNAP) as applicable to high level computer vision problems. The architecture consists of an array of identical cells each containing a content addressable memory, microprogram control, and a communication unit. The applications discussed in this correspondence are the two general techniques, discrete relaxation and dynamic programming. While the discrete relaxation is discussed with reference to scene labeling and edge interpretation, the dynamic programming is tuned for stereo.