myCopter: Enabling Technologies for Personal Aerial Transportation Systems: Project status after 2.5 years

Current means of transportation for daily commuting are reaching their limits during peak travel times, which results in waste of fuel and loss of time and money. A recent study commissioned by the European Union considers a personal aerial transportation system (PATS) as a viable alternative for transportation to and from work. It also acknowledges that developing such a transportation system should not focus on designing a new flying vehicle for personal use, but instead on investigating issues surrounding the implementation of the transportation system itself. This is the aim of European project myCopter: to determine the social and technological aspects needed to set up a transportation system based on personal aerial vehicles (PAVs). The project focuses on three research areas: human-machine interfaces and training, automation technologies, and social acceptance. Our extended abstract for inclusion in the conference proceedings and our presentation will focus on the achievements during the first 2.5 years of the 4-year project. These include the development of an augmented dynamic model of a PAV with excellent handling qualities that are suitable for training purposes. The training requirements for novice pilots are currently under development. Experimental evaluations on haptic guidance and human-in-the-loop control tasks have allowed us to start implementing a haptic Highway-in-the-Sky display to support novice pilots and to investigate metrics for objectively determining workload using psychophysiological measurements. Within the project, developments for automation technologies have focused on vision-based algorithms. We have integrated such algorithms in the control and navigation architecture of unmanned aerial vehicles (UAVs). Detecting suitable landing spots from monocular camera images recorded in flight has proven to reliably work off-line, but further work is required to be able to use this approach in real time. Furthermore, we have built multiple low-cost UAVs and equipped them with radar sensors to test collision avoidance strategies in real flight. Such algorithms are currently under development and will take inspiration from crowd simulations. Finally, using technology assessment methodologies, we have assessed potential markets for PAVs and challenges for its integration into the current transportation system. This will lead to structured discussions on expectations and requirements of potential PAV users

A shape-based account for holistic face processing

Faces are processed holistically, so selective attention to 1 face part without any influence of the others often fails. In this study, 3 experiments investigated what type of facial information (shape or surface) underlies holistic face processing and whether generalization of holistic processing to nonexperienced faces requires extensive discrimination experience. Results show that facial shape information alone is sufficient to elicit the composite face effect (CFE), 1 of the most convincing demonstrations of holistic processing, whereas facial surface information is unnecessary (Experiment 1). The CFE is eliminated when faces differ only in surface but not shape information, suggesting that variation of facial shape information is necessary to observe holistic face processing (Experiment 2). Removing 3-dimensional (3D) facial shape information also eliminates the CFE, indicating the necessity of 3D shape information for holistic face processing (Experiment 3). Moreover, participants show similar holistic processing for faces with and without extensive discrimination experience (i.e., own- and other-race faces), suggesting that generalization of holistic processing to nonexperienced faces requires facial shape information, but does not necessarily require further individuation experience. These results provide compelling evidence that facial shape information underlies holistic face processing. This shape-based account not only offers a consistent explanation for previous studies of holistic face processing, but also suggests a new ground-in addition to expertise-for the generalization of holistic processing to different types of faces and to nonface objects

Representational momentum in the motor system?

PURPOSE: If presented with a moving object which suddenly disappears observers usually misjudge the object's last seen position as being further forward along the path of motion. This effect, called representational momentum, can also be seen in objects that change size or shape. It has been argued that the effect is due to perceptual anticipation. We tested whether a similar effect is present in the motor system. METHODS: Using stereo computer graphics we presented cubes of different sizes on a CRT monitor. In each trial three cubes were successively presented for 200 msec with increasing or decreasing size (steps of 1 cm width difference). Ten participants either compared the last cube to a comparison cube (perceptual task) or grasped the cube using a virtual haptic setup (motor task). The setup consisted of two robot arms (Phantom TM) attached to index finger and thumb. The robot arms were controlled to create forces equivalent to the forces created by real objects. The CRT monitor was viewed via a mirror such that the visual position of the cubes matched the position of the virtual haptic objects. RESULTS: In the motor task participants opened their fingers by 1.1+/-0.4 mm wider if they grasped a cube that was preceded by smaller cubes than if they grasped a cube that was preceded by larger cubes. This is the well-known representational momentum effect. In the perceptual task the effect was reversed (-2.2+/-0.4 mm). The effects correlated between observers (r=.71, p=.02). CONCLUSIONS: It seems that a representational momentum occurs also in grasping tasks. The correlation between observers suggests that the motor effect is related to the perceptual effect. However, our perceptual task showed a reversed effect. Reasons for this discrepancy will be discussed

Beyond Faces and Expertise:Facelike Holistic Processing of Nonface Objects in the Absence of Expertise

Holistic processing-the tendency to perceive objects as indecomposable wholes-has long been viewed as a process specific to faces or objects of expertise. Although current theories differ in what causes holistic processing, they share a fundamental constraint for its generalization: Nonface objects cannot elicit facelike holistic processing in the absence of expertise. Contrary to this prevailing view, here we show that line patterns with salient Gestalt information (i.e., connectedness, closure, and continuity between parts) can be processed as holistically as faces without any training. Moreover, weakening the saliency of Gestalt information in these patterns reduced holistic processing of them, which indicates that Gestalt information plays a crucial role in holistic processing. Therefore, holistic processing can be achieved not only via a top-down route based on expertise, but also via a bottom-up route relying merely on object-based information. The finding that facelike holistic processing can extend beyond the domains of faces and objects of expertise poses a challenge to current dominant theories

Shape from X: Psychophysics and Computation

This chapter contains sections titled: The Many Routes to Shape, The Need for Integration, Shape From Stereo and Shading (Local Measurements) 1 , Shape from Shading and Texture (Global Measurements), Shape from Disparate Shading (Intensity-Based Stereo), Shape from Highlights 2 , Integration of Depth Modules, A Bayesian Framework for Cue Integration 3 , Final Remarks, Acknowledgments, Appendices, Reference

Holistic processing of static and moving faces

Humans' face ability develops and matures with extensive experience in perceiving, recognizing, and interacting with faces that move most of the time. However, how facial movements affect 1 core aspect of face ability-holistic face processing-remains unclear. Here we investigated the influence of rigid facial motion on holistic and part-based face processing by manipulating the presence of facial motion during study and at test in a composite face task. The results showed that rigidly moving faces were processed as holistically as static faces (Experiment 1). Holistic processing of moving faces persisted whether facial motion was presented during study, at test, or both (Experiment 2). Moreover, when faces were inverted to eliminate the contributions of both an upright face template and observers' expertise with upright faces, rigid facial motion facilitated holistic face processing (Experiment 3). Thus, holistic processing represents a general principle of face perception that applies to both static and dynamic faces, rather than being limited to static faces. These results support an emerging view that both perceiver-based and face-based factors contribute to holistic face processing, and they offer new insights on what underlies holistic face processing, how information supporting holistic face processing interacts with each other, and why facial motion may affect face recognition and holistic face processing differently. (PsycINFO Database Recor

Personally familiar faces: Higher precision of memory for idiosyncratic than for categorical information

Many studies have demonstrated that we can identify a familiar face on an image much better than an unfamiliar one, especially when various degradations or changes (e. g. image distortions or blurring, new illuminations) have been applied, but few have asked how different types of facial information from familiar faces are stored in memory. Here we investigated how well we remember personally familiar faces in terms of their identity, gender, and race. In three experiments, based on the faces personally familiar to our participants, we created sets of face morphs that parametrically varied the faces in terms of identity, sex or race, using a 3-dimensional morphable face model. For each familiar face, we presented those face morphs together with the original face and asked participants to pick the correct “real” face among morph distracters in each set. They were instructed to pick the face that most closely resembled their memory of that familiar person. We found that participants excelled in retrieving the correct familiar faces among the distracters when the faces were manipulated in terms of their idiosyncratic features (their identity information), but they were less sensitive to changes that occurred along the gender and race continuum. Image similarity analyses indicate that the observed difference cannot be attributed to different levels of image similarity between manipulations. These findings demonstrate that idiosyncratic and categorical face information is represented differently in memory, even for the faces of people we are very familiar with. Implications to current models of face recognition are discussed

Face recognition under varying pose: The role of texture and shape

Although remarkably robust, face recognition is not perfectly invariant to pose and viewpoint changes. It has been known since long, that the profile as well as the full-face view result in a recognition performance that is worse than a view from within that range. However, only few data exists that investigate this phenomenon in detail. This work intends to provide such data using a high angular resolution and a large range of poses. Since there are inconsistencies in the literature concerning these issues, we emphasize on the different role of the learning view and the testing view in the recognition experiment and on the role of information contained in the texture and in the shape of a face. Our stimuli were generated from laser-scanned head models and contained either the natural texture or only Lambertian shading and no texture. The results of our same/different face recognition experiments are: 1. Only the learning view but not the testing view effects the recognition performance. 2. For the textured faces the optimal learning view is closer to the full-face view than for the shaded faces. 3. For the shaded faces, we find a significantly better recognition performance for the symmetric view. The results can be interpreted in terms of different strategies to recover invariants from texture and from shading

Helilab User Manual: Human Behavior and Flight Data Acquisition and Analysis

We, here, introduce a flight simulator dedicated to collect both human behavior and flight data with high fidelity. This paper illustrates the current settings of the flight simulator, key issues in using the simulator, and the standard procedure of data acquisition and analysis