Following Futurism, we show how periodic motions can be represented by a small number of eigen-shapes that capture the whole dynamic mechanism of periodic motions. Spectral decomposition of a silhouette of an object in motion serves as a basis for behavior classification by principle component analysis. The boundary contour of the walking dog, for example, is first computed efficiently and accu...

We present a computationally efficient and robust shape from silhouette method based on topologyadaptive mesh deformation, which can produce accurate, smooth, and topologically consistent 3D mesh models of complex real objects. The deformation scheme is based on the conventional snake model coupled with local mesh transform operations that control the resolution and uniformity of the deformable...

Human activity recognition is an active research field in computer vision and image processing. In this paper we propose a robust rule-based method for the task of recognition of human activities and scenarios in video image sequences. The methodology uses a context-free grammar based representation scheme to represent human actions. The proposed system consists of three major steps. Initially ...

In this work, we introduce a model-based approach to extracting the silhouette of people in motion from stereo video sequences. To this end, we extend a purely stereo-based approach to tracking people proposed in earlier work. This approach is based on an implicit surface model of the body. It lets us accurately predict the silhouette’s location and, therefore, detect them more robustly. In tur...

This paper investigates performances of silhouette-based and depth-based gait authentication considering practical sensor settings where sensors are located in an environments afterwards and usually have to be located quite near to people. To realize fair comparison between different sensors and methods, we construct full-body volume of walking people by a multi-camera environment so as to reco...

In this work, we revise the problem of human body shape estimation from monocular imagery. Starting from a statistical human shape model that describes a body shape with shape parameters, we describe a novel approach to automatically estimate these parameters from a single input shape silhouette using semi-supervised learning. By utilizing silhouette features that encode local and global proper...

We present an algorithm to compute the silhouette set of a point cloud. Previous methods extract point set silhouettes by thresholding point normals, which can lead to simultaneous overand under-detection of silhouettes. We argue that additional information such as surface curvature is necessary to resolve these issues. To this end, we develop a local reconstruction scheme using Gabriel and int...

Biometrics is an important and automated method of recognizing persons based on a physiological or behavioral characteristic. Gait recognition biometric technologies becoming an important and highly secure identification and personal verification solutions. In biometric system and especially in gait recognition, one of the challenges that use object extraction is to create silhouette image. In ...

We present a method to solve the human silhouette tracking problem using 18 major human points. We used: a simple 2D model for the human silhouette, a linear prediction technique for initializing major points search, geometry anthropometric constraints for determining the search area and color measures for matching human body parts. In addition, we propose a method to solve the problem of human...

In this paper, we present a new multi-screen interactive environment. The system extracts a silhouette of the participant for driving the interaction using a method that overcomes the inherent problems associated with traditional chroma-keying, background subtraction, and rear-light projection methods. We present an approach for generating a robust silhouette of the participant using specialize...