10341811
A Two-Stage Template Approach to Person Detection in Thermal Imagery
We present a two-stage template-based method to detect people in widely varying thermal imagery. The approach initially performs a fast screening procedure using a generalized template to locate potential person locations. Next an AdaBoosted ensemble classifier using automatically tuned filters is employed to test the hypothesized person locations. We demonstrate and evaluate the approach using a challenging dataset of thermal imagery
10674834
Visual Categorization of Children and Adult Walking Styles
We present an approach for visual discrimination of children from adults in video using characteristic regularities present in their locomotion patterns. The framework employs computer vision to analyze correlated, scale invariant locomotion properties for classifying different styles of walking. Male and female subjects for the experiments include six children (3-5 yrs) and nine adults (30-52 yrs). For the analysis, we coordinate a minimalist point-representation of the human body with a space-time analysis of head and ankle trajectories to characterize the modality. Together the properties of relative stride length and stride frequency are shown to clearly differentiate children from adult walkers. The highly correlated log-linear relationships for the stride properties are exploited to reduce the categorization problem to a linear discrimination task. Using a trained two-class linear perceptron, we were able to achieve a correct classification rate of 93-95% on our dataset. Our approach emphasizing the natural modal behavior in human motion offers a useful and general methodology as the basis for designing efficient motion recognition systems using limited visual features.
7264850
Physically interactive story environments
Most interactive stories, such as hypertext narratives and interactive movies achieve an interactive "feel" by allowing the user to choose among multiple story paths. In this paper we discuss physically interactive environments with narrative structure in which the ability to choose among multiple story lines is replaced with having users, first, interact with the story characters in small, local "windows" of the narrative and, second, actively engage their bodies in movement, In particular, we found that compelling interactive narrative story systems can be perceived as highly responsive, engaging, and interactive even when the overall story has a single-path structure, in what we call a "less-choice, more-responsiveness" approach to the design of story-based interactive environments. We have also observed that unencumbering, rich sensor technology can facilitate user immersion in the experience as the story progresses--users can act as they typically would without worrying about manipulating a computer interface. To support these arguments, the paper describes the physical setup, the interactive story, the technology, and the user experience of four projects developed at the MIT Media Laboratory: KidsRoom, It/I, Personal Aerobics Trainer, and Swamped!
18551439
An adaptive focus-of-attention model for video surveillance and monitoring
In current video surveillance systems, commercial pan/tilt/zoom (PTZ) cameras typically provide naive (or no) automatic scanning functionality to move a camera across its complete viewable field. However, the lack of scene-specific information inherently handicaps these scanning algorithms. We address this issue by automatically building an adaptive, focus-of-attention, scene-specific model using standard PTZ camera hardware. The adaptive model is constructed by first detecting local human activity (i.e., any translating object with a specific temporal signature) at discrete locations across a PTZ camera’s entire viewable field. The temporal signature of translating objects is extracted using motion history images (MHIs) and an original, efficient algorithm based on an iterative candidacy-classification-reduction process to separate the target motion from noise. The target motion at each location is then quantified and employed in the construction of a global activity map for the camera. We additionally present four new camera scanning algorithms which exploit this activity map to maximize a PTZ camera’s opportunity of observing human activity within the camera’s overall field of view. We expect that these efficient and effective algorithms are implementable within current commercial camera systems.
1980573
The KidsRoom: A Perceptually-Based Interactive and Immersive Story Environment
The KidsRoom is a perceptually-based, interactive, narrative playspace for children. Images, music, narration, light, and sound effects are used to transform a normal child's bedroom into a fantasy land where children are guided through a reactive adventure story. The fully automated system was designed with the following goals: (1) to keep the focus of user action and interaction in the physical and not virtual space; (2) to permit multiple, collaborating people to simultaneously engage in an interactive experience combining both real and virtual objects; (3) to use computer-vision algorithms to identify activity in the space without requiring the participants to wear any special clothing or devices; (4) to use narrative to constrain the perceptual recognition, and to use perceptual recognition to allow participants to drive the narrative; and (5) to create a truly immersive and interactive room environment. We believe the KidsRoom is the first multi-person, fully-automated, interactive, narrative environment ever constructed using non-encumbering sensors. This paper describes the KidsRoom, the technology that makes it work, and the issues that were raised during the system's development.1 A demonstration of the project, which complements the material presented here and includes videos, images, and sounds from each part of the story is available at .
11408137
Building Adaptive Camera Models for Video Surveillance
We address the limited automatic scanning functionality of standard PTZ camera systems. We present an adaptive, scene-specific model using standard PTZ camera hardware. The adaptive model is constructed automatically by detecting human activity in motion history images (MHIs) using an iterative candidacy-classification-reduction process. The target motion is quantified and employed in the construction of a global activity map, which in turn is used to direct or navigate the camera
27293359
An Integrated Approach to Learning Bayesian Networks of Rules
Inductive Logic Programming (ILP) is a popular approach for learning rules for classification tasks. An important question is how to combine the individual rules to obtain a useful classifier. In some instances, converting each learned rule into a binary feature for a Bayes net learner improves the accuracy compared to the standard decision list approach [3,4,14]. This results in a two-step process, where rules are generated in the first phase, and the classifier is learned in the second phase. We propose an algorithm that interleaves the two steps, by incrementally building a Bayes net during rule learning. Each candidate rule is introduced into the network, and scored by whether it improves the performance of the classifier. We call the algorithm SAYU for Score As You Use. We evaluate two structure learning algorithms Naive Bayes and Tree Augmented Naive Bayes. We test SAYU on four different datasets and see a significant improvement in two out of the four applications. Furthermore, the theories that SAYU learns tend to consist of far fewer rules than the theories in the two-step approach.
14742091
On local pruning of association rules using directed hypergraphs
Here we propose an adaptive local pruning method for association rules. Our method exploits the exact mapping between a certain class of association rules, namely those whose consequents are singletons and backward directed hypergraphs (B-graphs). The hypergraph which represents the association rules is called an association rules network(ARN). Here we present a simple example of an ARN. We further prove several properties of the ARN and apply the results of our approach to two popular data sets.
4850818
Analysis of Weblog Link Structure - A Community Perspective
In this paper, we report a two level study on weblog link structures. At the micro level, we carried out an in-depth investigation of individual weblogs. Our goal was to obtain some preliminary understanding of the different types of links that might indicate underlying communities of bloggers. Complete and detailed link data was collected from eight weblogs followed by a variety of analyses. The result shows that both incoming and outgoings follow Zipf like distribution in terms of the sources of those links. These suggest clustering patterns (communities) within the whole blogspace. We also examine the temporal aspects of weblogs. The average life span of a weblog entry is fairly long in most of our sample cases. In addition, analysis on individual comment authors shows that in average, active comment authors maintain a rather long relationship with a certain weblog. It provides evidence that historical data may be useful in understanding weblog communities. On a larger scale, we developed a program to collect complete link data from large number of interconnected weblogs and performed cluster analysis on it. Communities with common topics are successfully extracted using those link data.
10894133
Octree textures
Texturing using a set of two dimensional image maps is an established and widespread practice. However, it has many limitations. Parameterizing a model in texture space can be very difficult, particularly with representations such as implicit surfaces, subdivision surfaces, and very dense or detailed polygonal meshes. This paper proposes the use of a new kind of texture based on an octree, which needs no parameterization other than the surface itself, and yet has similar storage requirements to 2D maps. In addition, it offers adaptive detail, regular sampling over the surface, and continuity across surface boundaries. The paper addresses texture creation, painting, storage, processing, and rendering with octree textures.
16145112
Mosaics of scenes with moving objects
Image mosaics are useful for a variety of tasks in vision and computer graphics. A particularly convenient way to generate mosaics is by 'stitching' together many ordinary photographs. Existing algorithms focus on capturing static scenes. This paper presents a complete system for creating visually pleasing mosaics in the presence of moving objects. There are three primary contributions. The first component of our system is a registration method that remains unbiased by movement-the Mellin transform is extended to register images related by a projective transform. Second an efficient method for finding a globally consistent registration of all images is developed. By solving a linear system of equations, derived from many pairwise registration matrices, we find an optimal global registration. Lastly, a new method of compositing images is presented. Blurred areas due to moving objects are avoided by segmenting the mosaic into disjoint regions and sampling pixels in each region from a single source image.