Towards Causal Effect Estimation of Emotional Labeling of Watched Videos

Emotions play a crucial role in human life, they are measured using many approaches. There are also many methodologies for emotion elicitation. Emotion elicitation through video watching is one important approach used to create emotion datasets. However, the causation link between video content and elicited emotions was not well explained by scientific research. In this article, we present an approach for computing the causal effect of video content on elicited emotion. The Do-Calculus theory was employed for computing causal inference, and a SCM (Structured Causal Model) was proposed considering the following variables: EEG signal, age, gender, video content, like/dislike, and emotional quadrant. To evaluate the approach, EEG data were collected from volunteers watching a sample of videos from the LIRIS-ACCEDE dataset. A total of 48 causal effects was statistically evaluated in order to check the causal impact of age, gender, and video content on liking and emotion. The results show that the approach can be generalized for any dataset that contains the variables of the proposed SCM. Furthermore, the proposed approach can be applied to any other similar dataset if an appropriate SCM is provided

Automatic annotation of tennis games: An integration of audio, vision, and learning

Fully automatic annotation of tennis game using broadcast video is a task with a great potential but with enormous challenges. In this paper we describe our approach to this task, which integrates computer vision, machine listening, and machine learning. At the low level processing, we improve upon our previously proposed state-of-the-art tennis ball tracking algorithm and employ audio signal processing techniques to detect key events and construct features for classifying the events. At high level analysis, we model event classification as a sequence labelling problem, and investigate four machine learning techniques using simulated event sequences. Finally, we evaluate our proposed approach on three real world tennis games, and discuss the interplay between audio, vision and learning. To the best of our knowledge, our system is the only one that can annotate tennis game at such a detailed level

A framework for P2P application development

Although Peer-to-Peer (P2P) computing has become increasingly popular over recent years, there still exist only a very small number of application domains that have exploited it on a large scale. This can be attributed to a number of reasons including the rapid evolution of P2P technologies, coupled with their often-complex nature. This paper describes an implemented abstraction framework that seeks to aid developers in building P2P applications. A selection of example P2P applications that have been developed using this framework are also presented

Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery

One of the main challenges for computer-assisted surgery (CAS) is to determine the intra-opera- tive morphology and motion of soft-tissues. This information is prerequisite to the registration of multi-modal patient-specific data for enhancing the surgeon’s navigation capabilites by observ- ing beyond exposed tissue surfaces and for providing intelligent control of robotic-assisted in- struments. In minimally invasive surgery (MIS), optical techniques are an increasingly attractive approach for in vivo 3D reconstruction of the soft-tissue surface geometry. This paper reviews the state-of-the-art methods for optical intra-operative 3D reconstruction in laparoscopic surgery and discusses the technical challenges and future perspectives towards clinical translation. With the recent paradigm shift of surgical practice towards MIS and new developments in 3D opti- cal imaging, this is a timely discussion about technologies that could facilitate complex CAS procedures in dynamic and deformable anatomical regions

The state of peer-to-peer network simulators

Networking research often relies on simulation in order to test and evaluate new ideas. An important requirement of this process is that results must be reproducible so that other researchers can replicate, validate and extend existing work. We look at the landscape of simulators for research in peer-to-peer (P2P) networks by conducting a survey of a combined total of over 280 papers from before and after 2007 (the year of the last survey in this area), and comment on the large quantity of research using bespoke, closed-source simulators. We propose a set of criteria that P2P simulators should meet, and poll the P2P research community for their agreement. We aim to drive the community towards performing their experiments on simulators that allow for others to validate their results