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Nigerian video-films on history: Love in Vendetta and the 1987 Kano riots
This paper considers a Nigerian video-film from 1996, Love in vendetta, featuring Zack Orji and inspired by the 1987 Kano riots, one of the many incidences of violent outbreaks which opposed Christians to Muslims in the 1980s and resulted in thousands of deaths, injuries and arrests. This Nigerian adaptation of Shakespeare's Romeo and Juliet presents two lovers: an Igbo man and a Hausa girl, who plan their marriage in the midst of strong family opposition on both sides. They eventually discover that their parents' attitude is the result of deep scars left by the 1987 Kano riots and bloodshed. Love eventually prevails, sending a message of hope to the whole country and heralding a time when ethnical and religious differences would be part of the Federation's rich cultural heritage
Demonstration of Negative Impedance Conversion for Bandwidth Extension in VLC
This work proposes and demonstrates the utility of a negative impedance converter (NIC) circuit, based on a common collector (CC) amplifier, for the generation of negative capacitance. The design principle of the proposed NIC is introduced, then a negative capacitance equals -200 pF is demonstrated using discrete devices constructed on a printed circuit board (PCB). The designed NIC is applied for the bandwidth extension of LEDs to enhance the achievable data rates in visible light communication (VLC) systems. The paper includes analytical derivations of the obtained negative capacitance as a function of circuit parameters and verifies this by both simulation and experimentally. Measurements show significant bandwidth extension by neutralising the bandwidth-limiting effect of the LED diffusion capacitance through the introduction of a parallel negative capacitance
On the merits of SVC-based HTTP adaptive streaming
HTTP Adaptive Streaming (HAS) is quickly becoming the dominant type of video streaming in Over-The-Top multimedia services. HAS content is temporally segmented and each segment is offered in different video qualities to the client. It enables a video client to dynamically adapt the consumed video quality to match with the capabilities of the network and/or the client's device. As such, the use of HAS allows a service provider to offer video streaming over heterogeneous networks and to heterogeneous devices. Traditionally, the H. 264/AVC video codec is used for encoding the HAS content: for each offered video quality, a separate AVC video file is encoded. Obviously, this leads to a considerable storage redundancy at the video server as each video is available in a multitude of qualities. The recent Scalable Video Codec (SVC) extension of H. 264/AVC allows encoding a video into different quality layers: by dowloading one or more additional layers, the video quality can be improved. While this leads to an immediate reduction of required storage at the video server, the impact of using SVC-based HAS on the network and perceived quality by the user are less obvious. In this article, we characterize the performance of AVC- and SVC-based HAS in terms of perceived video quality, network load and client characteristics, with the goal of identifying advantages and disadvantages of both options
Spatio-temporal Video Re-localization by Warp LSTM
The need for efficiently finding the video content a user wants is increasing
because of the erupting of user-generated videos on the Web. Existing
keyword-based or content-based video retrieval methods usually determine what
occurs in a video but not when and where. In this paper, we make an answer to
the question of when and where by formulating a new task, namely
spatio-temporal video re-localization. Specifically, given a query video and a
reference video, spatio-temporal video re-localization aims to localize
tubelets in the reference video such that the tubelets semantically correspond
to the query. To accurately localize the desired tubelets in the reference
video, we propose a novel warp LSTM network, which propagates the
spatio-temporal information for a long period and thereby captures the
corresponding long-term dependencies. Another issue for spatio-temporal video
re-localization is the lack of properly labeled video datasets. Therefore, we
reorganize the videos in the AVA dataset to form a new dataset for
spatio-temporal video re-localization research. Extensive experimental results
show that the proposed model achieves superior performances over the designed
baselines on the spatio-temporal video re-localization task
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