Figure 1: a) The exergame is based on a computer-controlled stationary exercycle and played while wearing a head-mounted display. b) A "self modelling cue" helps the player to identify a "ghost" avatar with their own previous performance. c) Low-intensity cycling and avoiding trucks during warm-up, recovery and cool-down phases. d) High-intensity race against the "ghost."
A key requirement for a sense of presence in Virtual Environments (VEs) is for a user to perceive space as naturally as possible. One critical aspect is distance perception. When judging distances, compression is a phenomenon where humans tend to underestimate the distance between themselves and target objects (termed egocentric or absolute compression), and between other objects (exocentric or relative compression). Results of studies in virtual worlds rendered through head mounted displays are striking, demonstrating significant distance compression error. Distance compression is a multisensory phenomenon, where both audio and visual stimuli are often compressed with respect to their distances from the observer. In this paper, we propose and test a method for reducing crossmodal distance compression in VEs. We report an empirical evaluation of our method via a study of 3D spatial perception within a virtual reality (VR) head mounted display. Applying our method resulted in more accurate distance perception in a VE at longer range, and suggests a modification that could adaptively compensate for distance compression at both shorter and longer ranges. Our results have a significant and intriguing implication for designers of VEs: an incongruent audiovisual display, i.e. where the audio and visual information is intentionally misaligned, may lead to better spatial perception of a virtual scene.
This work presents a novel hand pose estimation framework via intermediate dense guidance map supervision. By leveraging the advantage of predicting heat maps of hand joints in detection-based methods, we propose to use dense feature maps through intermediate supervision in a regression-based framework that is not limited to the resolution of the heat map. Our dense feature maps are delicately designed to encode the hand geometry and the spatial relation between local joint and global hand. The proposed framework significantly improves the stateof-the-art in both 2D and 3D on the recent benchmark datasets.
Objective: This article reports on the evaluation of The School Attendance Demonstration Project (SADP). SADP is an intervention aimed at improving the school attendance rates of 16-to 18-year-olds receiving public assistance. Method: Experimental group students attending school less than 80% of the time received a notice to attend an orientation for services. Students who continued to attend school less than 80%, did not attend the orientation, and could not show good cause for attendance were sanctioned. The study used a control group with random assignment. Results: Data show that in any month, more experimental group students met the attendance rule than did control group students. Logistic regression predicted that females, Hispanics, students from single-parent families, and those attending alternative schools had difficulty meeting attendance requirements. Conclusions: The findings suggest that at-risk teens need alternative strategies from sanctions to encourage school attendance.
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