The Deformable Parts Model (DPM) has recently emerged as a very useful and popular tool for tackling the intra-category diversity problem in object detection. In this paper, we summarize the key insights from our empirical analysis of the important elements constituting this detector. More specifically, we study the relationship between the role of deformable parts and the mixture model compone...

This paper describes a new approach to the tracking of complex shapes through image sequences, that combines deformable region models and deformable contours. A new deformable region model is presented: its optimisation is based on texture correlation and is constrained by the use of a motion model, such as rigid, aane or homographic. The use of texture information (versus edge information) not...

This paper addresses the problem of describing the significant intra and inter variability of 3D deformable structures within 3D image data sets. In pursuing it, a 3D probabilistic physically based deformable model is defined. The statistically learned deformable model captures the spatial relationships between the different objects surfaces, together with their shape variations. The structures...

Elastic graph matching has been proposed as a practical implementation of dynamic link matching, which is a neural network with dynamically evolving links between a reference model and an input image. Each node of the graph contains features that characterize the neighborhood of its location in the image. The elastic graph matching usually consists of two consecutive steps, namely a matching wi...

In this paper, we describe a real-time face-tracking algorithm. We start with single face tracking based on statistical color modeling and the deformable template. We then expand the algorithm to track multiple faces, possibly with occlusion, by constraining the speed and size changes of the faces. We test the algorithm on sequences with different occlusion patterns, and analyze the tracking pe...

In this paper, the level set algorithm is examined with a view to applications in image and video processing, and machine vision. Conventional parametric deformable models, which can be viewed as Lagrangian geometric models, where the boundary of the model has the ability to align itself with certain image features, are initially presented. This paper describes some of the problems associated w...

Previously, “Deformable organisms” were introduced as a novel paradigm for medical image analysis that uses artificial life modelling concepts. Deformable organisms were designed to complement the classical bottomup deformable models methodologies (geometrical and physical layers), with top-down intelligent deformation control mechanisms (behavioral and cognitive layers). However, a true physic...

We present a method that allows both autonomous and human-robot collaborative manipulation of deformable objects. The method does not require modeling and simulating deformation. Our method is based on the concept of diminishing rigidity, which we use to quickly compute an approximation to the Jacobian of the deformable object without using simulation. This Jacobian is used to drive the points ...

A real-time delivery of accurate soft-tissue intervention navigation information is one of the most crucial aspects for accepting the soft-tissue navigation systems for intra-operative use. Currently, soft-tissue navigation systems face some obstacles in terms of registration of the virtual navigation information on the deformable soft-tissue organ. Most of them perform a rigid registration bet...

Active Appearance Models (AAMs) are a well studied 2D deformable model. One recently proposed extension of AAMs to multiple images is the CoupledView AAM. Coupled-View AAMs model the 2D shape and appearance of a face in two or more views simultaneously. The major limitation of CoupledView AAMs, however, is that they are specific to a particular set of cameras, both in geometry and the photometr...