Research and Implementation for a Content-Based Video Playback System

2011 ◽  
pp. 392-398
Author(s):  
Zhang Lin ◽  
Duan Fu ◽  
Li Gang
Keyword(s):  
Video Playback

Video playback experiments on stickleback mate choice: female motivation and attentiveness to male colour cues

1995 ◽  
Vol 49 (6) ◽  
pp. 1559-1567 ◽  
Author(s):  
William J. Rowland ◽  
Kimberly J. Bolyard ◽  
Jennifer J. Jenkins ◽  
Jennifer Fowler
Keyword(s):  
Mate Choice ◽  
Video Playback ◽  
Playback Experiments

Video Playback Versus Live Stimuli for Assessing Mate Choice in a Pipefish

2006 ◽  
Vol 75 (4) ◽  
pp. 409-414 ◽  
Author(s):  
Sarah I. Robinson-Wolrath
Keyword(s):  
Mate Choice ◽  
Video Playback

scholarly journals Bitstream-Level Film Noise Cancellation for Damaged Video Playback

2014 ◽  
Vol E97.D (3) ◽  
pp. 562-572
Author(s):  
Sinwook LEE ◽  
Euee-seon JANG
Keyword(s):  
Noise Cancellation ◽  
Video Playback

scholarly journals A Proposed Adaptive Bitrate Scheme Based on Bandwidth Prediction Algorithm for Smoothly Video Streaming

2021 ◽  
Vol 27 (1) ◽  
pp. 112-129
Author(s):  
Saba Qasim Jabbar ◽  
Dheyaa Jasim Kadhim
Keyword(s):  
Video Streaming ◽  
Video Quality ◽  
Prediction Algorithm ◽  
Buffer Size ◽  
Video Playback ◽  
Buffer Occupancy ◽  
Simulation Results ◽  
Streaming Technology ◽  
The Impact ◽  
Buffer Structure

A robust video-bitrate adaptive scheme at client-aspect plays a significant role in keeping a good quality of video streaming technology experience. Video quality affects the amount of time the video has turned off playing due to the unfilled buffer state. Therefore to maintain a video streaming continuously with smooth bandwidth fluctuation, a video buffer structure based on adapting the video bitrate is considered in this work. Initially, the video buffer structure is formulated as an optimal control-theoretic problem that combines both video bitrate and video buffer feedback signals. While protecting the video buffer occupancy from exceeding the limited operating level can provide continuous video streaming, it may also cause a video bitrate oscillation. So the video buffer structure is adjusted by adding two thresholds as operating points for overflow and underflow states to filter the impact of throughput fluctuation on video buffer occupancy level. Then a bandwidth prediction algorithm is proposed for enhancing the performance of video bitrate adaptation. This algorithm's work depends on the current video buffer level, video bitrate of the previous segment, and iterative throughput measurements to predict the best video bitrate for the next segment. Simulation results show that reserving a bandwidth margin is better in adapting the video bitrate under bandwidth variation and then reducing the risk of video playback freezing. Simulation results proved that the playback freezing happens two times: firstly, when there is no bandwidth margin used and secondly, when the bandwidth margin is high while smooth video bitrate is obtained with moderate value. The proposed scheme is compared with other two schemes such as smoothed throughput rate (STR) and Buffer Based Rate (BBR) in terms of prediction error, QoE preferences, buffer size, and startup delay time, then the proposed scheme outperforms these schemes in attaining smooth video bitrates and continuous video playback.

scholarly journals Social learning and networks in Nestor parrots

2021 ◽  
Author(s):  
◽  
Daniel Donoghue
Keyword(s):  
Social Network ◽  
Social Learning ◽  
Tool Use ◽  
Social Information ◽  
Habitat Modification ◽  
Future Research ◽  
Video Playback ◽  
Food Aversion ◽  
Network Analyses ◽  
The Social

<p>Social learning and network analyses are theorised to be of great utility in the context of behavioural conservation. For example, harnessing a species’ capacity for social learning may allow researchers to seed useful information into populations, while network analyses could provide a useful tool to monitor community stability, and predict pathways of pathogen transfer. Thus, an understanding of how individuals learn and the nature of the social networks within a population could enable the development of new behavioural based conservation interventions for species facing rapid environmental change, such as human-induced habitat modification. Parrots, the most threatened avian order worldwide, are notably underrepresented in the social learning and social network literature. This thesis addresses this knowledge gap by exploring social learning and networks using two endangered species of parrot; kākā (Nestor meridionalis) and kea (Nestor notabilis). The first study explores social learning of tool use in captive kea, using a trained kea demonstrator. The results from this experiment indicate that both social learning and play behaviour facilitated the uptake of tool use, and suggests that kea are highly sensitive to social information even when presented with complex tasks. The second study assesses whether wild kākā can socially learn novel string-pulling and food aversion behaviours from video playbacks of conspecific demonstrators. Although there was no evidence to indicate that kākā learn socially, these individuals also show no notable reaction to video playback of a familiar predator. Therefore, these results are likely due to difficulties in interpreting information on the screens, and not necessarily a reflection of their ability to perceive social information. In the final study, social network analysis (SNA) was performed to map social connectivity within wellington’s urban kākā population. SNA indicates that kākā form non-random social bonds, selectively associating with some individuals more than others, and also show high levels of dissimilarity in community composition at different feeding sites. Taken together, these results provide rare empirical evidence of social learning in a parrot species and suggest that even complicated seeded behaviours can quickly spread to other individuals. These findings may also be indicative of the difficulties in conducting video playback experiments in wild conditions, which is an area in need of future research. Overall, these findings contribute to the very limited body of research on social learning and networks in parrots, and provide information of potential value in the management of these species.</p>

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