International audienceAutomatic recognition of facial expressions is a challenging problem specially for low spatial resolution facial images. It has many potential applications in human-computer interactions, social robots, deceit detection, interactive video and behavior monitoring. In this study we present a novel framework that can recognize facial expressions very efficiently and with high accuracy even for very low resolution facial images. The proposed framework is memory and time efficient as it extracts texture features in a pyramidal fashion only from the perceptual salient regions of the face. We tested the framework on different databases, which includes Cohn-Kanade (CK+) posed facial expression database, spontaneous expressions of MMI facial expression database and FG-NET facial expressions and emotions database (FEED) and obtained very good results. Moreover, our proposed framework exceeds state-of-the-art methods for expression recognition on low resolution images
We present a novel and generic framework for the recognition of body expressions using human postures. Motivated by the state of the art from the domain of psychology, our approach recognizes expression by analyzing sequence of pose. Features proposed in this article are computationally simple and intuitive to understand. They are based on visual cues and provide in-depth understanding of body postures required to recognize body expressions. We have evaluated our approach on different databases with heterogeneous movements and body expressions. Our recognition results exceeds state of the art for some database and for others we obtain results at par with state of the art.
8 pagesInternational audienceCirdo project is intended to establish new healthcare systems to ensure the safety at home of seniors and people with decreasing independence. In particular, extending "e-lio" (http://www.technosens.fr/) device, Cirdo aims to develop an audio/video-based system which makes it possible for elderly to live with a sufficient degree of autonomy. To achieve this goal, generic purposes on video analysis and audio processing are discussed and implemented in the same process. Audio and video analysis algorithms are launched simultaneously and thinks to GPU implementation, the tasks are done in real time. To comply with the requirements set out in the Cirdo project namely: respect privacy and preserve personal data, the processing tasks is performed through background tasks, without any human intrusion. In order to have different types of fall for our experiences, multiple scenarios were designed and performed by several persons. Besides the technical aspect, the project also focuses on generic technology validation by potential users and their human environment (family, caregivers/care takers...). Psychological and ergonomic assessment on the use of services developed was conducted. It focused on the usefulness, usability and accessibility and acceptance of the tool. This evaluation was completed by critical investigation of knowledge acquired by professionals (geriatricians, caregivers school and associations)
. Figure 1: The bottom row shows the virtual face animated by retargeting expressions from the source face (top row).
AbstractWe present a method for transferring facial animation in real-time. The source animation may be an existing 3D animation or 2D data providing by a video tracker or a motion capture system. Based on two sets of feature points manually selected on the source and target faces (the only manual work required), a RBF network is trained and provides a geometric transformation between the two faces. At each frame, the RBF transformation is applied on the new feature points positions of the source face, resulting in new positions for target feature points according with the expression of the source face and the morphology of the target face. According to their displacements along time, we deform the target mesh on the GPU with the linear blend skinning (LBS) method. In order to make our approach attractive to novice user, we propose a procedural technique to automatically rig the target face by generating vertices weights for the skinning deformation. To summarize, our method provides interactive expression transfer with a minimal human intervention during setup and accepts various kind of animation sources.
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