Sung Chun Lee

Extraction and integration of window in a 3D building model from ground view images

Details of the building facades are needed for high quality fly-through visualization or simulation applications. Windows form a key structure in the detailed facade reconstruction. In this paper, given calibrated facade texture (i.e. the rectified texture), we extract and reconstruct the 3D window structure of the building. We automatically extract windows (rectangles in the rectified image) using a profile projection method, which exploits the regularity of the vertical and horizontal window placement. We classify the extracted windows using 2D dimensions and image texture information. The depth of the extracted windows is automatically computed using window classification information and image line features. A single ground view image is enough to compute 3D depths of the facade windows in our approach.

Automatic pose estimation of complex 3D building models

3D models of urban sites with geometry and facade textures are needed for many planning and visualization applications. Approximate 3D wireframe model can be derived from aerial images but detailed textures must be obtained from ground level images. Integrating such views with the 3D models is difficult as only small parts of buildings may be visible in a single view. We describe a method that uses two or three vanishing points, and three 3D to 2D line correspondences to estimate the rotational and translational parameters of the ground level cameras. The valid set of multiple combinations of 3D to 2D line pairs is chosen by a hypotheses generation and evaluation Some experimental results are presented.

Hierarchical abnormal event detection by real time and semi-real time multi-tasking video surveillance system

In this paper, we describe how to detect abnormal human activities taking place in an outdoor surveillance environment. Human tracks are provided in real time by the baseline video surveillance system. Given trajectory information, the event analysis module will attempt to determine whether or not a suspicious activity is currently being observed. However, due to real-time processing constrains, there might be false alarms generated by video image noise or non-human objects. It requires further intensive examination to filter out false event detections which can be processed in an off-line fashion. We propose a hierarchical abnormal event detection system that takes care of real time and semi-real time as multi-tasking. In low level task, a trajectory-based method processes trajectory data and detects abnormal events in real time. In high level task, an intensive video analysis algorithm checks whether the detected abnormal event is triggered by actual humans or not.

Interactive 3D building modeling using a hierarchical representation

Modeling and visualization of city scenes is important for many applications including entertainment and urban mission planning. Models covering wide areas can be efficiently constructed from aerial images. However, only roof details are visible from aerial views and ground views are needed to provide details of the building facades for high quality fly-through visualization or simulation applications. Different data sources provide different levels of necessary detail knowledge. We need a method that integrates the various levels of data. We propose a hierarchical representation of 3D building models for urban areas that integrates different data sources including aerial and ground view images. Each data source gives us different details and each level of the model has its own application as well. Through the hierarchical representation of 3D building models, large area site modeling can be done efficiently and cost-effectively. This proposal suggests efficient approaches for acquiring each level model and demonstrates some results of each level including the integration results.

Integrating ground and aerial views for urban site modeling

3D models of urban sites with good geometry and facade textures are needed for many planning and visualization applications. Approximate wireframe can be derived from aerial images but detailed textures must be obtained from ground level images. Integrating such views with the 3D models is difficult as only small parts of buildings may be visible in a single view. We describe a method that uses two or three vanishing points, not necessarily from orthogonal sets of parallel lines, and a small number of point correspondences to estimate the intrinsic and extrinsic parameters of the ground level cameras. Experimental results from some buildings are presented.

Modeling 3-D complex buildings with user assistance

An effective 3D method incorporating user assistance for modeling complex buildings is proposed. This method utilizes the connectivity and similar structure information among unit blocks in a multi-component building structure, to enable the user to incrementally construct models of many types of buildings. The system attempts to minimize the time and the number of user interactions needed to assist an existing automatic system in this task. Several examples are presented that demonstrate significant improvement and efficiency compared with other approaches and with purely manual systems.

Robust camera calibration tool for video surveillance camera in urban environment

Video surveillance applications such as smart room and security system are prevailing nowadays. Camera calibration information (e.g. camera position, orientation, and focal length) is very useful for various surveillance systems because it can provide scene knowledge and limit search space for object detection or tracking. In this paper, we describe a camera calibration tool that does not require any calibration object or specific geometric objects by using vanishing points. In urban environment, vanishing points are easily obtainable since there exist many parallel lines such as street lines, light poles, buildings, etc in either outdoor or indoor scene images. Experimental results from various surveillance cameras are presented.

Geodec: Enabling Geospatial Decision Making

The rapid increase in the availability of geospatial data has motivated the effort to seamlessly integrate this information into an information-rich and realistic 3D environment. However, heterogeneous data sources with varying degrees of consistency and accuracy pose a challenge to such efforts. We describe the geospatial decision making (GeoDec) system, which accurately integrates satellite imagery, three-dimensional models, textures and video streams, road data, maps, point data and temporal data. The system also includes a glove-based user interface

CLEAR'07 Evaluation of USC Human Tracking System for Surveillance Videos

This paper presents the evaluation results of a system for tracking humans in surveillance videos. Moving blobs are detected based on adaptive background modeling. A shape based multi-view human detection system is used to find humans in moving regions. The detected responses are associated to infer the human trajectories. The shaped based human detection and tracking is further enhanced by a blob tracker to boost the performance on persons at a long distance from the camera. Multi-threading techniques are used to speedup the process. Results are given on the video test set of the CLEAR-VACE surveillance human tracking evaluation task.

Speed Performance Improvement of Vehicle Blob Tracking System

A speed performance improved vehicle tracking system on a given set of evaluation videos of a street surveillance system is presented. We implement multi-threading technique to meet the requirement of real-time performance which demanded in the practical surveillance systems. Through multi-threading technique, we can accomplish near real-time performance. An analysis of results is also presented.