The World of Fast Moving Objects

The notion of a Fast Moving Object (FMO), i.e. an object that moves over a distance exceeding its size within the exposure time, is introduced. FMOs may, and typically do, rotate with high angular speed. FMOs are very common in sports videos, but are not rare elsewhere. In a single frame, such objects are often barely visible and appear as semi-transparent streaks. A method for the detection and tracking of FMOs is proposed. The method consists of three distinct algorithms, which form an efficient localization pipeline that operates successfully in a broad range of conditions. We show that it is possible to recover the appearance of the object and its axis of rotation, despite its blurred appearance. The proposed method is evaluated on a new annotated dataset. The results show that existing trackers are inadequate for the problem of FMO localization and a new approach is required. Two applications of localization, temporal super-resolution and highlighting, are presented

Beds, Handkerchiefs, and Moving Objects in Othello

This paper argues that a viewer watching Othello in an unfamiliar language, without subtitles, can more narrowly focus upon the life of things in the play and in adaptations or appropriations of it. Jane Bennett argues in Vibrant Matter for a renewed vital materialism — an emphasis on objects in the world and on attributing agency or actantial ability to them. In Shakespeare's Othello two objects dominate the play: most obviously, the handkerchief; less obviously, because it is sometimes part of the stage, the bed in which Desdemona is smothered. I consider the ways in which a South Indian, a North Indian "Bollywood" and an Italian teen movie adaptation of Othello permit these objects to act expressively. These adaptations (Kaliyattam; Omkara; Iago) indigenize and transform both the handkerchief and the "tragic loading" of the bed, in the last case turning (or returning) the Shakespearean source from tragedy to comedy

Efficient MaxCount and threshold operators of moving objects

Calculating operators of continuously moving objects presents some unique challenges, especially when the operators involve aggregation or the concept of congestion, which happens when the number of moving objects in a changing or dynamic query space exceeds some threshold value. This paper presents the following six d-dimensional moving object operators: (1) MaxCount (or MinCount), which finds the Maximum (or Minimum) number of moving objects simultaneously present in the dynamic query space at any time during the query time interval. (2) CountRange, which finds a count of point objects whose trajectories intersect the dynamic query space during the query time interval. (3) ThresholdRange, which finds the set of time intervals during which the dynamic query space is congested. (4) ThresholdSum, which finds the total length of all the time intervals during which the dynamic query space is congested. (5) ThresholdCount, which finds the number of disjoint time intervals during which the dynamic query space is congested. And (6) ThresholdAverage, which finds the average length of time of all the time intervals when the dynamic query space is congested. For these operators separate algorithms are given to find only estimate or only precise values. Experimental results from more than 7,500 queries indicate that the estimation algorithms produce fast, efficient results with error under 5%

Moving Objects in the Hubble Ultra Deep Field

We identify proper motion objects in the Hubble Ultra Deep Field (UDF) using the optical data from the original UDF program in 2004 and the near-infrared data from the 128-orbit UDF 2012 campaign. There are 12 sources brighter than I=27 mag that display >3sigma significant proper motions. We do not find any proper motion objects fainter than this magnitude limit. Combining optical and near-infrared photometry, we model the spectral energy distribution of each point-source using stellar templates and state-of-the-art white dwarf models. For I<27 mag, we identify 23 stars with K0-M6 spectral types and two faint blue objects that are clearly old, thick disk white dwarfs. We measure a thick disk white dwarf space density of 0.1-1.7 E-3 per cubic parsec from these two objects. There are no halo white dwarfs in the UDF down to I=27 mag. Combining the Hubble Deep Field North, South, and the UDF data, we do not see any evidence for dark matter in the form of faint halo white dwarfs, and the observed population of white dwarfs can be explained with the standard Galactic models.Comment: ApJ, in pres