Public safety practitioners increasingly use video for object recognition tasks. These end users need guidance regarding
how to identify the level of video quality necessary for their application. The quality of video used in public safety
applications must be evaluated in terms of its usability for specific tasks performed by the end user.
The Public Safety Communication Research (PSCR) project performed a subjective test as one of the first in a series to
explore visual intelligibility in video-a user's ability to recognize an object in a video stream given various conditions.
The test sought to measure the effects on visual intelligibility of three scene parameters (target size, scene motion, scene
lighting), several compression rates, and two resolutions (VGA (640x480) and CIF (352x288)). Seven similarly sized
objects were used as targets in nine sets of near-identical source scenes, where each set was created using a different
combination of the parameters under study. Viewers were asked to identify the objects via multiple choice questions.
Objective measurements were performed on each of the scenes, and the ability of the measurement to predict visual
intelligibility was studied.
To develop accurate objective measurements (models) for video quality assessment, subjective data is traditionally
collected via human subject testing. The ITU has a series of Recommendations that address methodology for performing
subjective tests in a rigorous manner. These methods are targeted at the entertainment application of video. However,
video is often used for many applications outside of the entertainment sector, and generally this class of video is used to
perform a specific task. Examples of these applications include security, public safety, remote command and control,
and sign language. For these applications, video is used to recognize objects, people or events. The existing methods,
developed to assess a person's perceptual opinion of quality, are not appropriate for task-based video. The Institute for
Telecommunication Sciences, under a program from the Department of Homeland Security and the National Institute for
Standards and Technology's Office of Law Enforcement, has developed a subjective test method to determine a person's
ability to perform recognition tasks using video, thereby rating the quality according to the usefulness of the video
quality within its application. This new method is presented, along with a discussion of two examples of subjective tests
using this method.
Most digital signal processing methods have an underlying assumption of regularly-spaced data samples. However, many real-world data collection techniques generate data sets which are not sampled at evenly-spaced intervals, or which may have significant data dropout problems. Therefore, a method of interpolation is needed to model the signal on an even grid of arbitrary granularity. We propose the interpolation of nonuniformly sampled fields using a least- square fit of the data to a wavelet basis in a multiresolution setting.
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