The paper discusses comparative generic sentences As are F-er than Bs—girls do better than boys in grade school, for example—which pose severe problems for extant accounts. In their stead, the paper proposes reconceiving the LF of generic sentences as more closely akin to that of sentences containing non-generic plurals, paradigmatically plural definite descriptions. Given this one crucial chan...

This paper presents a method for tracking human head in cluttered scenes to achieve robustness to occlusions and environment change by introducing inheritance and evolution concept into tracking system. Different from most works on tracking where detection and tracking are loosely coupled, we view the essence of object detection and tracking as a process of modeling object class classifier (in ...

Generic H A SKELL exploits the promising new incarnation of generic programming due to Hinze. Apart from extending the programming language Haskell, Hinze-style polytypism offers a simple approach to defining generic functions which are applicable to types of all kinds. Here we explore a number of simple but significant extensions to Hinze’s ideas which make generic programming both more expres...

Natural scenes in a video stream contain rich collections of visual transformations. In this paper, a generic neural network is built to learn visual invariance from videos in an unsupervised manner. We use temporal coherence to learn both visual transformations and features with complex invariances. Without fine-tuning with labels, our invariant features are superior for classifying objects in...

Complex networks in natural, social and technological systems generically exhibit an abundance of rich information. Extracting meaningful structural features from data is one of the most challenging tasks in network theory. Many methods and concepts have been proposed to address this problem such as centrality statistics, motifs, community clusters and backbones, but such schemes typically rely...

This paper is about automatically annotating images with keywords in order to be able to retrieve images with text searches. Our approach is to model keywords such as 'mountain' and 'city' in terms of visual features that were extracted from images. In contrast to other algorithms, each specific keyword-model considers not only its own training data but also the whole training set by utilizing ...

Reconstructing a 3D model of a human face from a video sequence is an important problem in computer vision, with applications to recognition, surveillance, multimedia etc. However, the quality of 3D reconstructions using structure from motion (SfM) algorithms is often not satisfactory. One common method of overcoming this problem is to use a generic model of a face. Existing work using this app...

Generic object recognition by a computer is strongly required in various fields like robot vision and image retrieval in recent years. Conventional methods use Conditional Random Field (CRF) that recognizes the class of each region using the features extracted from the local regions and the class co-occurrence between the adjoining regions. However, there is a problem that CRF tends to fall int...

This paper describes a method to extract facial features from front and side views for 3D facial model creation by modifying a 3D generic head model. Front and side views of a person's face are taken simultaneously by two cameras under the same geometric condition. The side view (profile) is first analyzed using a DP template matching to extract vertical locations of nose and mouth. Then, by us...

Datatype-generic programming is natural and useful in dependently typed languages such as Agda. However, datatype-generic libraries Agda are not reused much they should be, because traditionally work only on datatypes decoded from a library’s own version of datatype descriptions; this means that different generic cannot be used together, do native datatypes, which preferred by the practical pro...