HeadOn: Real-time Reenactment of Human Portrait Videos

We propose HeadOn, the first real-time source-to-target reenactment approach for complete human portrait videos that enables transfer of torso and head motion, face expression, and eye gaze. Given a short RGB-D video of the target actor, we automatically construct a personalized geometry proxy that embeds a parametric head, eye, and kinematic torso model. A novel real-time reenactment algorithm employs this proxy to photo-realistically map the captured motion from the source actor to the target actor. On top of the coarse geometric proxy, we propose a video-based rendering technique that composites the modified target portrait video via view- and pose-dependent texturing, and creates photo-realistic imagery of the target actor under novel torso and head poses, facial expressions, and gaze directions. To this end, we propose a robust tracking of the face and torso of the source actor. We extensively evaluate our approach and show significant improvements in enabling much greater flexibility in creating realistic reenacted output videos.Comment: Video: https://www.youtube.com/watch?v=7Dg49wv2c_g Presented at Siggraph'1

Experimental approaches to referential domains and the on-line processing of referring expressions in unscripted conversation

Peer reviewedPublisher PD

Design, Implementation, and Performance Study of an Open Source Eye-Control System to Pilot a Parrot AR.Drone Quadrocopter

Natural user interface is a fairly new concept in the field of human-computer interaction. It is the idea of using every day natural human behaviors and actions to control a device. An example of a natural user interface is touch control technology in smartphones, tablets, and new laptops. The interaction is more direct when compared to artificial input devices like a keyboard and mouse. Though natural user interface devices might not perform as well as standard input devices for certain applications, for other applications they are now the de facto standard. A new user interface that is poised to be the next natural user interface in human-computer interaction is eye-control, or the ability to control an interface with just the user’s eyes using technology that has been around for a long time called eye trackers. The problem for much of the existence of eye trackers is the cost. Most modern commercial eye trackers cost anywhere between $10,000 and$40,000, and that is too expensive for regular consumers to buy and use. In this paper, we build a low cost system for eye-control using an open source program called ITU Gaze Tracker. In the process, we developed an interface which allows a user to pilot a Parrot AR.Drone quadrocopter using just their gaze. In this explorative study, we explore the performance of this eye-control system to keyboard control in the operation of an AR.Drone around an obstacle course. We collected certain performance metrics like lap completion time

MANAGEMENT OF CONSUMERS’ ATTENTION – WHAT CAN THE ADVERTISER DO TO SURVIVE THE MEDIA REVOLUTION

I know half the money I spend on advertising is wasted, I just don’t know which half joked John Wanamaker, who created the first department store in 1876 [15]. In spite of the passageof time Wanamaker’s saying is still in force. However, it may change soon thanks to coming intobeing of new discipline ââ¬â neuromarketing, which is combination of advertisements’ artistry andsciences (inter alia neuropsychology, cognitive psychology, neuroimaging, cognitive science,psycholinguistics). Neuromarketing postulates using fMRI, EEG, EMG or eye tracking techniquesfor the purpose of recognising consumers’ preferences toward specific goods and brands as well asmechanisms concerning decision-making process related to purchases. The goal of neuromarketingis to obtain the information - the human brain’s responses, which marketing stimuli (advertisement)is effective.the media, neuromarketing, advertisement

Mapping dynamic interactions among cognitive biases in depression

Depression is theorized to be caused in part by biased cognitive processing of emotional information. Yet, prior research has adopted a reductionist approach that does not characterize how biases in cognitive processes such as attention and memory work together to confer risk for this complex multifactorial disorder. Grounded in affective and cognitive science, we highlight four mechanisms to understand how attention biases, working memory difficulties, and long-term memory biases interact and contribute to depression. We review evidence for each mechanism and highlight time- and context-dependent dynamics. We outline methodological considerations and recommendations for research in this area. We conclude with directions to advance the understanding of depression risk, cognitive training interventions, and transdiagnostic properties of cognitive biases and their interactions

LIMBUSTRACK: STABLE EYE-TRACKING IN IMPERFECT LIGHT CONDITIONS

We are aware of only one serious effort at development of a cheap, accurate, wearable eye tracker: the open source openEyes project. However, its method of ocular feature detection is such that it is prone to failure in variable lighting conditions. To address this deficiency, we have developed a cheap wearable eye tracker. At the heart of our development are novel techniques that allow operation under variable illumination

Assessing the effects of work zone configurations on drivers\u27 visual attention

This study assessed the effects of two different work zone configurations on driver’s visual attention by eye movement monitoring. A driving simulator study was conducted with thirty participants. Variations in traffic density and warning sign placement distance were added to the merge configurations to simulate the real time situation. A 2 x 2 x 3 within-subjects factorial design was used for this research. The independent variables used in this study were (1) merge configuration [(i) Conventional Lane Merge (CLM) and (ii) Joint Lane Merge (JLM)], (2) traffic density [(i) high and (ii) low] and (3) distance between traffic signs [(i) standard distance, (ii) 25% reduction from standard and (iii) 25% increase from standard]. The dependent variable used for this study was the total number of eye movements (gaze) of the participants towards the three mirrors (rear view, left side view and right side view), and towards ‘other areas’ such as dash board, warning signs, environment, and other vehicles etc., were analyzed. Results from the research show that, the total number of gazes at mirrors and ‘other areas’ in CLM and JLM are nearly the same and they are not significantly different (p value: \u3e0.05). Changes in traffic density and sign placement distances have a significant effect on number of gazes at mirrors and ‘other areas’ (p value: \u3c0.05). Gender and driving experience have a significant effect on number of gazes at mirrors, but not at ‘other areas’. Reducing the sign placement distances by 25% from the standard distances does not show any significant effect on the number of gazes at mirrors, however it shows an increase in the number of gazes at ‘other areas’ by nearly 11.6%. An increase in sign placement distances by 25% from the standard distances, show an increase in number of gazes at mirrors by nearly 16.9%, while it does not show any significant effect on the number of gazes at the ‘other areas’

Grand Challenges of Traceability: The Next Ten Years

In 2007, the software and systems traceability community met at the first Natural Bridge symposium on the Grand Challenges of Traceability to establish and address research goals for achieving effective, trustworthy, and ubiquitous traceability. Ten years later, in 2017, the community came together to evaluate a decade of progress towards achieving these goals. These proceedings document some of that progress. They include a series of short position papers, representing current work in the community organized across four process axes of traceability practice. The sessions covered topics from Trace Strategizing, Trace Link Creation and Evolution, Trace Link Usage, real-world applications of Traceability, and Traceability Datasets and benchmarks. Two breakout groups focused on the importance of creating and sharing traceability datasets within the research community, and discussed challenges related to the adoption of tracing techniques in industrial practice. Members of the research community are engaged in many active, ongoing, and impactful research projects. Our hope is that ten years from now we will be able to look back at a productive decade of research and claim that we have achieved the overarching Grand Challenge of Traceability, which seeks for traceability to be always present, built into the engineering process, and for it to have "effectively disappeared without a trace". We hope that others will see the potential that traceability has for empowering software and systems engineers to develop higher-quality products at increasing levels of complexity and scale, and that they will join the active community of Software and Systems traceability researchers as we move forward into the next decade of research