21,398 research outputs found
Synthetic aperture imaging with intensity-only data
We consider imaging the reflectivity of scatterers from intensity-only data
recorded by a single moving transducer that both emits and receives signals,
forming a synthetic aperture. By exploiting frequency illumination diversity,
we obtain multiple intensity measurements at each location, from which we
determine field cross-correlations using an appropriate phase controlled
illumination strategy and the inner product polarization identity. The field
cross-correlations obtained this way do not, however, provide all the missing
phase information because they are determined up to a phase that depends on the
receiver's location. The main result of this paper is an algorithm with which
we recover the field cross-correlations up to a single phase that is common to
all the data measured over the synthetic aperture, so all the data are
synchronized. Thus, we can image coherently with data over all frequencies and
measurement locations as if full phase information was recorded
Circulant temporal encoding for video retrieval and temporal alignment
We address the problem of specific video event retrieval. Given a query video
of a specific event, e.g., a concert of Madonna, the goal is to retrieve other
videos of the same event that temporally overlap with the query. Our approach
encodes the frame descriptors of a video to jointly represent their appearance
and temporal order. It exploits the properties of circulant matrices to
efficiently compare the videos in the frequency domain. This offers a
significant gain in complexity and accurately localizes the matching parts of
videos. The descriptors can be compressed in the frequency domain with a
product quantizer adapted to complex numbers. In this case, video retrieval is
performed without decompressing the descriptors. We also consider the temporal
alignment of a set of videos. We exploit the matching confidence and an
estimate of the temporal offset computed for all pairs of videos by our
retrieval approach. Our robust algorithm aligns the videos on a global timeline
by maximizing the set of temporally consistent matches. The global temporal
alignment enables synchronous playback of the videos of a given scene
Recommended from our members
Synthetic Aperture Imaging With Intensity-Only Data.
We consider imaging the reflectivity of scatterers from intensity-only data
recorded by a single moving transducer that both emits and receives signals,
forming a synthetic aperture. By exploiting frequency illumination diversity,
we obtain multiple intensity measurements at each location, from which we
determine field cross-correlations using an appropriate phase controlled
illumination strategy and the inner product polarization identity. The field
cross-correlations obtained this way do not, however, provide all the missing
phase information because they are determined up to a phase that depends on the
receiver's location. The main result of this paper is an algorithm with which
we recover the field cross-correlations up to a single phase that is common to
all the data measured over the synthetic aperture, so all the data are
synchronized. Thus, we can image coherently with data over all frequencies and
measurement locations as if full phase information was recorded
A parallel algorithm to calculate the costrank of a network
We developed analogous parallel algorithms to implement CostRank for distributed memory parallel computers using multi processors. Our intent is to make CostRank calculations for the growing number of hosts in a fast and a scalable way. In the same way we intent to secure large scale networks that require fast and reliable computing to calculate the ranking of enormous graphs with thousands of vertices (states) and millions or arcs (links). In our proposed approach we focus on a parallel CostRank computational architecture on a cluster of PCs networked via Gigabit Ethernet LAN to evaluate the performance and scalability of our implementation. In particular, a partitioning of input data, graph files, and ranking vectors with load balancing technique can improve the runtime and scalability of large-scale parallel computations. An application case study of analogous Cost Rank computation is presented. Applying parallel environment models for one-dimensional sparse matrix partitioning on a modified research page, results in a significant reduction in communication overhead and in per-iteration runtime. We provide an analytical discussion of analogous algorithms performance in terms of I/O and synchronization cost, as well as of memory usage
- …