35,628 research outputs found
HLVU : A New Challenge to Test Deep Understanding of Movies the Way Humans do
In this paper we propose a new evaluation challenge and direction in the area
of High-level Video Understanding. The challenge we are proposing is designed
to test automatic video analysis and understanding, and how accurately systems
can comprehend a movie in terms of actors, entities, events and their
relationship to each other. A pilot High-Level Video Understanding (HLVU)
dataset of open source movies were collected for human assessors to build a
knowledge graph representing each of them. A set of queries will be derived
from the knowledge graph to test systems on retrieving relationships among
actors, as well as reasoning and retrieving non-visual concepts. The objective
is to benchmark if a computer system can "understand" non-explicit but obvious
relationships the same way humans do when they watch the same movies. This is
long-standing problem that is being addressed in the text domain and this
project moves similar research to the video domain. Work of this nature is
foundational to future video analytics and video understanding technologies.
This work can be of interest to streaming services and broadcasters hoping to
provide more intuitive ways for their customers to interact with and consume
video content
Sketching Cuts in Graphs and Hypergraphs
Sketching and streaming algorithms are in the forefront of current research
directions for cut problems in graphs. In the streaming model, we show that
-approximation for Max-Cut must use space;
moreover, beating -approximation requires polynomial space. For the
sketching model, we show that -uniform hypergraphs admit a
-cut-sparsifier (i.e., a weighted subhypergraph that
approximately preserves all the cuts) with
edges. We also make first steps towards sketching general CSPs (Constraint
Satisfaction Problems)
Crowdsourced Live Streaming over the Cloud
Empowered by today's rich tools for media generation and distribution, and
the convenient Internet access, crowdsourced streaming generalizes the
single-source streaming paradigm by including massive contributors for a video
channel. It calls a joint optimization along the path from crowdsourcers,
through streaming servers, to the end-users to minimize the overall latency.
The dynamics of the video sources, together with the globalized request demands
and the high computation demand from each sourcer, make crowdsourced live
streaming challenging even with powerful support from modern cloud computing.
In this paper, we present a generic framework that facilitates a cost-effective
cloud service for crowdsourced live streaming. Through adaptively leasing, the
cloud servers can be provisioned in a fine granularity to accommodate
geo-distributed video crowdsourcers. We present an optimal solution to deal
with service migration among cloud instances of diverse lease prices. It also
addresses the location impact to the streaming quality. To understand the
performance of the proposed strategies in the realworld, we have built a
prototype system running over the planetlab and the Amazon/Microsoft Cloud. Our
extensive experiments demonstrate that the effectiveness of our solution in
terms of deployment cost and streaming quality
Flow profiling of a surface acoustic wave nanopump
The flow profile in a capillary gap and the pumping efficiency of an acoustic
micropump employing Surface Acoustic Waves is investigated both experimentally
and theoretically. Such ultrasonic surface waves on a piezoelectric substrate
strongly couple to a thin liquid layer and generate an internal streaming
within the fluid. Such acoustic streaming can be used for controlled agitation
during, e.g., microarray hybridization. We use fluorescence correlation
spectroscopy and fluorescence microscopy as complementary tools to investigate
the resulting flow profile. The velocity was found to depend on the applied
power somewhat weaker than linearly and to decrease fast with the distance from
the ultrasound generator on the chip.Comment: 12 pages 20 figure
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