A Video Timeline with Bookmarks and Prefetch State for Faster Video Browsing

International audienceReducing seek latency by predicting what the users will access is important for user experience, particularly during video browsing, where users seek frequently to skim through a video. Much existing research strived to predict user access pattern more accurately to improve the prefetching hit rate. This paper proposed a different approach whereby the prefetch hit rate is improved by biasing the users to seek to prefetched content with higher probability, through changing the video player user interface. Through a user study, we demonstrated that our player interface can lead to up to 4$\times$ more seeks to bookmarked segments and reduce seek latency by 40\%, compared to a video player interface commonly used today. The user study also showed that the user experience and the understanding of the video content when browsing is not compromised by the changes in seek behavior.

The use of deception in dementia-care robots: Should robots tell "white lies" to limit emotional distress?

With projections of ageing populations and increasing rates of dementia, there is need for professional caregivers. Assistive robots have been proposed as a solution to this, as they can assist people both physically and socially. However, caregivers often need to use acts of deception (such as misdirection or white lies) in order to ensure necessary care is provided while limiting negative impacts on the cared-for such as emotional distress or loss of dignity. We discuss such use of deception, and contextualise their use within robotics.Comment: 3 pages, to be published in Proceedings of the 11th International Conference on Human-Agent Interaction (ACM HAI'23

Critical Video Quality for Distributed Automated Video Surveillance

Large-scale distributed video surveillance systems pose new scalability challenges. Due to the large number of video sources in such systems, the amount of bandwidth required to transmit video streams for monitoring often strains the capability of the network. On the other hand, large-scale surveillance systems often rely on computer vision algorithms to automate surveillance tasks. We observe that these surveillance tasks present an opportunity for trade-off between the accuracy of the tasks and the bit rate of the video being sent. This paper shows that there exists a sweet spot, which we term critical video quality that can be used to reduce video bit rate without significantly affecting the accuracy of the surveillance tasks. We demonstrate this point by running extensive experiments on standard face detection and face tracking algorithms. Our experiments show that face detection works equally well even if the quality of compression is significantly reduced, and face tracking still works even if the frame rate is reduced to 6 frames per second. We further develop a prototype video surveillance system to demonstrate this idea. Our evaluation shows that we can achieve up to 29 times reduction in video bit rate when detecting faces and 16 times reduction when tracking faces. This paper also proposes a formal rate-accuracy optimization framework which can be used to determine appropriate encoding parameters in distributed video surveillance systems that are subjected to either bandwidth constraints or accuracy constraints

Comparing How a Chatbot References User Utterances from Previous Chatting Sessions: An Investigation of Users' Privacy Concerns and Perceptions

Chatbots are capable of remembering and referencing previous conversations, but does this enhance user engagement or infringe on privacy? To explore this trade-off, we investigated the format of how a chatbot references previous conversations with a user and its effects on a user's perceptions and privacy concerns. In a three-week longitudinal between-subjects study, 169 participants talked about their dental flossing habits to a chatbot that either, (1-None): did not explicitly reference previous user utterances, (2-Verbatim): referenced previous utterances verbatim, or (3-Paraphrase): used paraphrases to reference previous utterances. Participants perceived Verbatim and Paraphrase chatbots as more intelligent and engaging. However, the Verbatim chatbot also raised privacy concerns with participants. To gain insights as to why people prefer certain conditions or had privacy concerns, we conducted semi-structured interviews with 15 participants. We discuss implications from our findings that can help designers choose an appropriate format to reference previous user utterances and inform in the design of longitudinal dialogue scripting.Comment: 10 pages, 3 figures, to be published in Proceedings of the 11th International Conference on Human-Agent Interaction (ACM HAI'23

Streaming of Plants in Distributed Virtual Environments

International audienceJust as in the real world, plants are important objects in virtual world for creating pleasant and realistic environments, especially those involving natural scenes. As such, much effort has been made in realistic modeling of plants. As the trend moves towards networked and distributed virtual environment, however, the current models are inadequate as they are not designed for progressive transmissions. In this paper, we fill in this gap by proposing a progressive representation for plants based on generalized cylinders. To facilitate the transmission of the plants, we quantify the visual contribution of each branch and use this weight in packet scheduling. We show the efficiency of our representations and effectiveness of our packet scheduler through simulations

Pushing the Envelope: Solving Hard Multimedia Problems with Crowdsourcing

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