From the Publisher: 
The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

Cell phones and other portable devices are equipped with a variety of technologies by which existing functionality can be improved, and new functionality can be provided. Some relate to visual search capabilities, and determining appropriate actions responsive to different image inputs. Others relate to processing of image data. Still others concern metadata generation, processing, and representation. Yet others relate to coping with fixed focus limitations of cell phone cameras, e.g., in reading digital watermark data. Still others concern user interface improvements. A great number of other features and arrangements are also detailed.

Methods and Systems for Content Processing

Newness and distinctiveness is claimed in the features of ornamentation as shown inside the broken line circle in the accompanying representation.

Display screen or portion thereof with graphical user interface

A mobile terminal including a body; a touchscreen provided to a front and extending to side of the body and configured to display content; and a controller configured to detect one side of the body comes into contact with one side of an external terminal, display a first area on the touchscreen corresponding to a contact area of the body and the external terminal and a second area including the content, receive an input of moving the content displayed in the second area to the first area, display the content in the first area, and share the content in the first area with the external terminal.

Mobile terminal and method for controlling the same

/pdf/remote-sensing-of-the-environment-4yfxjaaswe.pdf

Remote sensing of the environment

A compound-eye imaging device comprises: an optical lens array with integrated optical lenses; a stop member; a photodetector array for imaging multiple images formed by the optical lenses; and a light shielding block for partitioning a space between the two arrays into a matrix of spaces, with light-passing holes, so as to prevent lights emitted from the optical lenses from interfering each other. The light shielding block is formed of unit plates in a stack, each having light-passing windows. Each light-passing window has blackened surface. The unit plates in the stack are alternately reversed upside down and left-right so as to allow the horizontal positions of the light-passing windows for forming each light-passing hole through the unit plates in the stack to be alternately offset in depth direction of the hole, thereby forming an irregular inner wall surface which serves as a light scattering surface to prevent e.g. ghost.

Compound-Eye Imaging Device

The authors have proposed an architecture for a compact image-capturing system called TOMBO (thin observation module by bound optics), which uses compound-eye imaging for a compact hardware configuration [Appl. Opt. 40, 1806 (2001)]. The captured compound image is decomposed into a set of unit images, then the pixels in the unit images are processed with digital processing to retrieve the target image. A new method for high-resolution image reconstruction, called a pixel rearrange method, is proposed. The relation between the target object and the captured signals is estimated and utilized to rearrange the original pixel information. Experimental results show the effectiveness of the proposed method. In the experimental TOMBO system, the resolution obtained is four times higher than that of the unit image that did not undergo reconstruction processing.

/pdf/reconstruction-of-a-high-resolution-image-on-a-compound-eye-436wvvlla0.pdf

Reconstruction of a high-resolution image on a compound-eye image-capturing system.

Typical compound-eye imaging systems consist of multiple lenslets arranged regularly because of the advantages of these arrangements, such as simplicity in design, fabrication, and data processing Such a regular arrangement, however, exhibits strong fluctuation of the imaging performance over the object distance To solve this problem, irregularity is introduced, and this approach is applied to a compound-eye imaging system called thin observation module by bound optics (TOMBO) An efficient design method for improving the imaging performance is presented Simulation results, including the peak signal-to-noise ratio of the super-resolved images, confirm the effectiveness of the proposed method

https://iopscience.iop.org/article/10.1143/APEX.3.022501/pdf

Irregular Lens Arrangement Design to Improve Imaging Performance of Compound-Eye Imaging Systems

A three-dimensional object imaging device comprises a compound-eye imaging unit and an image reconstructing unit for reconstructing an image of a three-dimensional object based on multiple unit images captured by the imaging unit. Based on the unit images obtained by the imaging unit, the image reconstructing unit calculates a distance (hereafter “pixel distance”) between the object and the imaging unit for each pixel forming the unit images, and rearranges the unit images pixel-by-pixel on a plane at the pixel distance to create a reconstructed image. Preferably, the image reconstructing unit sums a high-frequency component reconstructed image created from the multiple unit images with a lower noise low-frequency component unit image selected from low-frequency component unit images created from the multiple unit images so as to form a reconstructed image of the three-dimensional object. This makes it possible to obtain a reconstructed image with high definition easily by a simple process.

Three-Dimensional Object Imaging Device

An imaginary object plane is set in front of an imaging device body (plane setting step). A part of optical conditions of optical lenses are changed as variables, and positions of points (pixel observation points) on the imaginary object plane where lights coming from pixels of a solid-state imaging element and back-projected through the optical lenses are calculated (pixel observation point calculating step). The dispersion in position of the calculated pixel observation points is evaluated (evaluating step). Finally, a set of values of the variables giving maximum evaluated dispersion of the calculated pixel observation points is determined as optimum optical condition of the optical lenses (condition determining step). This reduces the number of pixels which image the same portions of the target object, making it possible to reduce portions of the same image information in multiple unit images, and to stably obtain a reconstructed image having a high definition.

Yasuo Masaki

Papers

Compound-Eye Imaging Device

Reconstruction of a high-resolution image on a compound-eye image-capturing system.

Irregular Lens Arrangement Design to Improve Imaging Performance of Compound-Eye Imaging Systems

Three-Dimensional Object Imaging Device

Optical condition design method for a compound-eye imaging device