Iview User Manual

[Matilda Equiluz]

2COMMAND LINE INTERFACE - connect via serial cable to XG firewall device open putty and log in to the CLI > Select "5. Device Management" > Select "4. Flush Device Reports" and follow the instructions

MY PROBLEM: These are instructions in user manuals but the problem is this is not working for me, the reports are still on the device no matter what I do. Anyone with similar experience?

iView MediaPro helps you organize and display a variety of file types: images, movies, sounds, fonts, illustrations, text files, and HTML pages. Files can be labeled, categorized, voice annotated, renamed, copied, or moved individually or in batches.

An iView MediaPro catalog holds related images or files. You create a new blank catalog by selecting New from the File menu. You create a filled catalog by selecting Import Media from the File menu. The two submenus let you import individual files or entire folders of files or (if you use OS X) images stored in a digital camera. The main iView MediaPro catalog window has three views (selected via tabs): Content, Thumbnail, and Media. All three views contain tabs and a toolbar at the top (these can be hidden); information on the selected file(s) on the left side (which also can be hidden); a viewing area to the right that contains a file list, thumbnails, or a full-sized image (or font sample); and a status bar on the bottom with a pop-up menu containing choices relevant to the current view.

As with any good cataloging application, iView MediaPro lets you organize, sort, and select files using a variety of methods and criteria. You can select a subset of images, for example, and perform batch operations on the subset. These operations can include creating labels, adding or changing file information such as keywords, playing a slide show, rotating images, and so on.

iView MediaPro can help with other aspects of file management. It offers version control for each catalog: the original files are backed up into a designated folder (one per catalog). A log file tracks file additions or removals from the catalog. Version Control also tracks file changes and stores each version. This feature is especially useful in a workgroup environment. Users can add comments to changed versions, and Version Control records the identity of each user who edited a file.

iView MediaPro also includes image modification tools. The JPEG rotate tool is on the toolbar and in the Action menu. You can rotate images by 90 or 180 degrees. iView MediaPro also contains a somewhat misnamed Calibrator palette. This palette is active only in Media view. The tools (from left to right) are for cropping; adjusting sharpness, brightness, and contrast; adjusting hue, saturation, and lightness; color correcting (balance); and inverting image colors (negative to positives). You have the option of overwriting the original file, making a backup before overwriting the original file, or creating a new file that is added to your catalog along with the original.

Images can be saved as an HTML (Web) gallery. The program creates an index page with thumbnail images and media pages for the full-sized images. You can adjust thumbnail and image sizes, bit depths, and JPEG quality.

iView MediaPro can convert images, movies, and sounds between different formats. It uses QuickTime or other third-party applications for these conversions. The big advantage of using iView MediaPro is that it can perform batch conversions. You can also save conversion options for reuse with other sets of files.

AppleScript is fully supported by iView MediaPro. It comes with 22 scripts organized into 6 groups in the AppleScript menu. AppleScripts are useful for certain types of batch tasks such as file renaming and automatic caption creation. You can add scripts by placing them into the Plug-ins:Scripts folder. You also can control iView MediaPro with applets or AppleScripts written within other applications.

I experienced numerous application crashes (with Type 2 and 3 errors) and a few full system crashes while reviewing iView MediaPro. Some crashes were random, while others were reproducible. An example of the latter is a full system crash that occurs if you press the Home key while iView MediaPro is importing a folder of images. After iView MediaPro crashed with a Type 2 or 3 error, restarting was necessary to run the application. (Note: The iView MediaPro may be more stable under OS X. There are known conflicts in OS 9 with Logitech Optical wheel mouse driver and OSA menu. However, I was not running either extension.)

The application comes with a 66-page user manual and an 18-page quick start guide. Both are available as PDF files in the downloaded version. The PDF user manual has bookmark links. Neither PDF manual has an index, and neither has links in the table of contents or within the documents. A printed copy of the user manual comes with the boxed (CD-ROM) version. The user manual adequately describes most features of iView MediaPro. Its AppleScript section is very skimpy, however.

The iView Web site has tutorials and a support area containing frequently asked questions, a user forum, and a query submission form. There is no telephone, fax, or live chat room support. I did not test the speed or accuracy of replies to support queries.

iPhoto is OS X-only and free. It is clumsier than iView, much slower, and does not let you choose your own filenames or folder structure for storing the images. It is generally not as featured as iView MediaPro, but it has the advantage of direct integration with various Apple services.

Abstract The goal of structured prediction is to build machine learning models that predict relational information that itself has structure, such as being composed of multiple interrelated parts. These models, which reflect prior knowledge, task-specific relations, and constraints, are used in fields including computer vision, speech recognition, natural language processing, and computational biology. They can carry out such tasks as predicting a natural language sentence, or segmenting an image into meaningful components.These models are expressive and powerful, but exact computation is often intractable. A broad research effort in recent years has aimed at designing structured prediction models and approximate inference and learning procedures that are computationally efficient. This volume offers an overview of this recent research in order to make the work accessible to a broader research community. The chapters, by leading researchers in the field, cover a range of topics, including research trends, the linear programming relaxation approach, innovations in probabilistic modeling, recent theoretical progress, and resource-aware learning.

Abstract The analysis and understanding of human movement is central to many applicationssuch as sports science, medical diagnosis and movie production. The ability to automatically monitor human activity in security sensitive areas such as airports,lobbies or borders is of great practical importance. Furthermore, automaticpose estimation from images leverages the processingand understanding of massive digital libraries available on the Internet. We build upon a model based approach where the human shape is modelled with a surface meshand the motion is parametrized by a kinematic chain. We then seek for the poseof the model that best explains the available observations coming from different sensors.In a first scenario, we consider a calibrated mult-iview setup in an indoor studio. To obtain very accurateresults, we propose a novel tracker that combines information coming from video and asmall set of Inertial Measurement Units (IMUs). We do so by locally optimizing a jointenergy consisting of a term that measures the likelihood of the video data and a termfor the IMU data. This is the first work to successfully combine video and IMUsinformation for full body pose estimation. When compared to commercial marker based systemsthe proposed solution is more cost efficient and less intrusive for the user. In a second scenario, we relax the assumption of an indoor studio and we tackle outdoor sceneswith background clutter, illumination changes, large recording volumes and difficult motions of people interacting with objects. Again, we combine information from video and IMUs. Here we employ a particle based optimization approachthat allows us to be more robust to tracking failures. To satisfy the orientation constraintsimposed by the IMUs, we derive an analytic Inverse Kinematics (IK) procedure to sample from the manifoldof valid poses. The generated hypothesis come from a lower dimensional manifold and therefore the computationalcost can be reduced. Experiments on challenging sequences suggest the proposed tracker can be appliedto capture in outdoor scenarios. Furthermore, the proposed IK sampling procedure can be usedto integrate any kind of constraints derived from the environment.Finally, we consider the most challenging possible scenario: pose estimation of monocular images. Here, we argue that estimating the pose to the degree of accuracy as in an engineered environment istoo ambitious with the current technology. Therefore, we propose to extract meaningful semantic information aboutthe pose directly from image features in a discriminative fashion. In particular, we introduce posebitswhich are semantic pose descriptors about the geometric relationships between parts in the body. The experimentsshow that the intermediate step of inferring posebits from images can improve pose estimation from monocular imagery. Furthermore, posebits can be very useful as input feature for many computer visionalgorithms.

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