VISION4HCI 2016 Abstracts


Full Papers
Paper Nr: 2
Title:

Toward a Real Time View-invariant 3D Action Recognition

Authors:

Mounir Hammouche, Enjie Ghorbel, Anthony Fleury and Sébastien Ambellouis

Abstract: In this paper we propose a novel human action recognition method, robust to viewpoint variation, which combines skeleton- and depth-based action recognition approaches. For this matter, we first build several base classifiers, to independently predict the action performed by a subject. Then, two efficient combination strategies, that take into account skeleton accuracy and human body orientation, are proposed. The first is based on fuzzy switcher where the second uses a combination between fuzzy switcher and aggregation. Moreover, we introduce a new algorithm for the estimation of human body orientation. To perform the test we have created a new Multiview 3D Action public dataset with three viewpoint angles (30°,0°,-30°). The experimental results show that an efficient combination strategy of base classifiers improves the accuracy and the computational efficiency for human action recognition.

Paper Nr: 3
Title:

Insert Your Own Body in the Oculus Rift to Improve Proprioception

Authors:

Manuela Chessa, Lorenzo Caroggio, Huayi Huang and Fabio Solari

Abstract: A natural interaction in virtual reality environments, in particular when wearing head-mounted-displays, is often prevented by the lack of a visual feedback about the user’s own body. This paper aims to create a virtual environment, in which the user can visually perceive his/her own body, and can interact with the virtual objects, by using a virtual body that replicates his/her movements. To this aim, we have set up an affordable virtual reality system, which combines the Oculus Rift head-mounted-display, a Microsoft Kinect, and a Leap Motion, in order to recreate inside the virtual environments a first-person avatar, who replicates the movements of the user’s full-body and the fine movements of his/her fingers and hands. By acting in such an environment, the user is able to perceive him/herself thus improving his/her experience in the virtual reality. Here, we address and propose a solution to the issues related to the integration of the different devices, and to the alignment and registration of their reference systems. Finally, the effectiveness of the proposed system is assessed through an experimental session, in which several users report their feeling by answering to a 5-points Likert scale questionnaire.

Short Papers
Paper Nr: 1
Title:

Speed-up Line Detection Approach for Large-size Document Images by Parallel Pixel Scanning and Hough Space Minimization

Authors:

H. Waruna H. Premachandra, Chinthaka Premachandra, Chandana Dinesh Parape and Hiroharu Kawanaka

Abstract: Hough transform (HT) is typically used to detect lines in images, but that method is slow due to its use of voting-based parameter detection; detecting lines in large document images can take dozens of minutes. Nonetheless HT is very effective at detecting lines, so we investigate methods for fast HT-based line detection of large document images by minimizing Hough space processing and reducing the image area used for line detection with parallel pixel scanning and local image domain analysis. We conduct experiments to confirm the effectiveness of the proposed method using appropriate large documents images. The results show a significant computational time reduction as compared to conventional methods.

Paper Nr: 4
Title:

An Oculus Rift based Exergame to Improve Awareness in Disabled People

Authors:

Manuela Chessa, Gabriele Balocchi, Michela Busi, Antonio Novellino and Fabio Solari

Abstract: In this paper we present an exergame, based on the Oculus Rift head-mounted-display, with the aim of improving spatial awareness in young people with cognitive deficits. The scope is to create a virtual environment that should be immersive, and should allow a natural human-computer interaction, without creating discomfort to the users. The exergame is simple, since the aim of the present work is not to create a photo-realistic scenario, but a familiar environment in which to play and exercise cognitive abilities. To measure and track the movements of the users’ legs, in order to simulate the walking in the environment in a safe way, an additional sensor, the Playstation Move, has been embedded into the system. Finally, the system has been tested with some disabled subjects, who confirmed the usability of the exergame and a general positive feeling with such an immersive virtual reality.