This article presents the development of an interactive, augmented reality, and collaborative Pong game. In our approach, an overhead projector displays the game on the floor, showing the game's current state as it develops. In the meantime, a computer vision system sensing throughout an overhead depth camera detects the players and their movements. We tested our system in a roofed but wall-less environment. Our assessment of the gaming experience includes natural language processing on interviews with children and qualitative analysis of their verbal responses.

Nonverbal communication is an intrinsic part in daily face-to-face meetings. A frequently observed behavior during social interactions is mirroring, in which one person tends to mimic the attitude of the counterpart. This paper shows that a computer vision system could be used to predict the perception of competence in dyadic interactions through the automatic detection of mirroring events. To prove our hypothesis, we developed: (1) A social assistant for mirroring detection, using a wearable device which includes a video camera and (2) an automatic classifier for the perception of competence, using the number of nodding gestures and mirroring events as predictors. For our study, we used a mixed-method approach in an experimental design where 48 participants acting as customers interacted with a confederated psychologist. We found that the number of nods or mirroring events has a significant influence on the perception of competence. Our results suggest that: (1) Customer mirroring is a better predictor than psychologist mirroring; (2) the number of psychologist's nods is a better predictor than the number of customer's nods; (3) except for the psychologist mirroring, the computer vision algorithm we used worked about equally well whether it was acquiring images from wearable smartglasses or fixed cameras.

In this document, we study the problem of optimally placing a mixture of directional and omnidirectional cameras. In our solution, the workspace is represented by an occupancy grid map [1]. Then, using surface-projected workspace and camera perception models, we develop a binary integer programming algorithm. The results of the algorithm are applied successfully to a variety of simulated scenarios.

In this work a proposal to model the activity at vehicular intersections with the aim of detecting unusual events is presented. Using the particular constraints that this kind of scenarios provide, we develop methods to detect, track, and model the activity of moving objects. Our description of activity is based on the local definition, at each pixel, of a multimodal model for the direction of motion. During operation, a particular observation is compared with the learned model. Our experiments give clear indication that the proposed scheme has a good performance in detecting such unusual events as vehicles running on red light and making forbidden turns.

In this paper, an iterative framework for projection-based image sequence registration to be used by a non-holonomic mobile robot is introduced. Since obtaining complete registration has shown to be difficult and error prone, it is claimed that it is worth pursuing trying to gather at least partial and qualitative information from projections. A tracking method is adapted to select and track features between projections. Some results are shown with sequences of images taken when a mobile robot was heading forward, approximately along its optical axis, and rotating approximately around its optical center. It is shown that is possible to interpret camera motion from the projection of individual frames in an image stream.

In this paper, we introduce the concept of Visual Memory Maps (VMM). A VMM is an ordered accumulation of visual information, classified to avoid redundancy and to provide fast retrieval through the comparison of newly acquired images with stored memories. We use VbIM to give some low level visual capabilities to mobile robots. To do this, a mobile robot is guided through a path while it takes snapshots. The image stream is then converted into a VMM. Two problems that surge are both the representation of the image stream and the comparison of new frames with the VMM. In this research, we use Principal Component Analysis to have a compact representation and to index the image stream, and introduce a registration scheme to search for correspondence directly in the space of the principal components.

It is important to set landmarks when a robot needs to navigate in a certain environment and to measure its own location; however, it has not been discussed well how to arrange landmarks in the optimal way until now. We, therefore, demonstrate the possibility of design of the optimal arrangement of artificial landmarks. First, we make it clear the optimization problem with regard to the arrangement of landmarks. Second, as one example of the artificial landmarks, we introduce a signboard system. Third, we propose a methodology to evaluate arrangement of landmarks assuming an obstacled rectangular environment. Fourth, we apply the algorithm of spatial competition to the optimal arrangement of landmarks. Finally, simulation results indicate that even though our method is not global optimization approach we can obtain closely optimal and practical arrangement with the minimum number of landmarks which satisfies the necessary condition.