Editing and deformation of irregular meshes have become standard tools in geometric modeling. Most approaches try to preserve low-level differential properties of the surface during editing, whereas the global structure and shape of the features are not explicitly taken into account. In this paper, we introduce a feature-driven editing approach that puts global structural properties of the shap...

This paper presents a visual architecture able to identify salient regions in a visual scene and to use them to focus on interesting locations. It is inspired by the ability of natural vision systems to perform a differential processing of spatial frequencies both in time and space and to focus their attention on a very local part of the visual scene. The present paper analyzes how this differe...

In this study, we present the results of classification experiments of induced dog barks in different contexts of behaviour. We applied four validation schemes to trained models in order to determine the level of individuals dependency for context classification. We did an analysis based on feature selection techniques to determine the best acoustic low-level descriptors for this task. Results ...

The AAAI-90 Workshop on Qualitative Vision was organized into seven sessions, with each session focusing on a specific topic. The first session was on the approaches and psychophysical bases of qualitative vision, addressing the question of what is qualitative vision. The second session presented work on motion and navigation. The topics of the next four sessions were qualitative shape extracti...

For high-level feature extraction, we submitted 4 automatic runs: Fudan.Global: this run is based on global features of keyframes. Fudan.Local: this run is based on local features of keyframes. Fudan.Rerank: this run is based on local features and spatial information of keyframes. Fudan.Fusion: this run is based on the fusion of global and local features of keyframes. Focus of our system was on...

The idea of computational error correction has been around for over half a century. The motivation has largely been to mitigate unreliable devices, manufacturing defects or harsh environments, primarily as a mandatory measure to preserve reliability, or more recently, as a means to lower energy by allowing soft errors to occasionally creep. While residue codes have shown great promise for this ...

Novel and simplified methods for determining low-level states of student behavior and predicting affective states enable tutors to better respond to students. The Many Eyes Word Tree graphics is used to understand and analyze sequential patterns of student states, categorizing raw quantitative indicators into a limited number of discrete sates. Used in combination with sensor predictors, we dem...

In this paper a general and e cient approach for representing and classifying image sequences by Hid den Markov Models HMMs is presented A consis tent modeling of spatial and temporal information is achieved by extracting di erent low level image fea tures These implicitly convert the image intensities into probability density values while preserving the ge ometry of the image The resulting so ...

We take part in the short text conversation task at NTCIR-12. We employ a semantic-based retrieval method to tackle this problem, by calculating textual similarity between posts and comments. Our method applies a rich-feature model to match post-comment pairs, by using semantic, grammar, n-gram and string features to extract high-level semantic meanings of text.

We participated in the high-level feature extraction task in TRECVID 2007. This paper describes the details of our system for the task. For feature extraction, we propose an EMD-based bag-of-feature method to exploit visual/spatial information, and utilize WordNet to expand semantic meanings of text to boost up the generalization of detectors. We also explore audio features and extract the moti...