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Persistent surveillance of large geographic areas from unmanned aerial vehicles allows us to learn much about the daily activities in the region of interest. Nearly all of the approaches addressing tracking in this imagery are detection-based and rely on background subtraction or frame differencing to provide detections. This, however, makes it difficult to(More)
Recent work on multi-object tracking has shown the promise of tracklet-based methods. In this work we present a method which infers tracklets then groups them into tracks. It overcomes some of the disadvantages of existing methods, such as the use of heuristics or non-realistic constraints. The main idea is to formulate the data association problem as(More)
We present a method for recognizing a vehicle's make and model in a video clip taken from an arbitrary viewpoint. This is an improvement over existing methods which require a front view. In addition, we present a Bayesian approach for establishing accurate correspondences in multiple view geometry. We take a model-based, top-down approach to classify(More)
Wide area aerial surveillance data has recently proliferated and increased the demand for multi-object tracking algorithms. However, the limited appearance information on every target creates much ambiguity in tracking and increases the difficulty of removing false target detections. In this work we propose to learn motion patterns in wide area scenes and(More)
In this work we consider the problem of tracking objects from a moving airborne platform in wide area surveillance through long occlusions and/or when their motion is unpredictable. The main idea is to take advantage of the known 3D scene structure to estimate a dynamic occlusion map, and to use the occlusion map to determine traffic entry and exit into(More)
We present the design and implementation of an activity recognition system in wide area aerial video surveillance using Entity Relationship Models (ERM). In this approach, finding an activity is equivalent to sending a query to a Relational DataBase Management System (RDBMS). By incorporating reference imagery and Geographic Information System (GIS) data,(More)
Wide Area Aerial Surveillance (WAAS) imagery is captured by an array of smaller sensors sharing an optical center, instead of one large sensor. It is desirable to generate a single image (mosaic) from the sensor array, since it simplifies higher level vision tasks. It is important that the mosaic be of high quality, without noticeable seams, and be(More)
We present the design and implementation of an activity recognition system for wide area aerial video surveillance using Entity Relationship Models (ERM). In this approach, finding an activity is equivalent to sending a query to the Relational DataBase Management System (RDBMS). By incorporating reference imagery and Geographic Information System (GIS)(More)
We address the estimation of human poses from a single view point in images and sequences. This is an important problem with a range of applications in human computer interaction, security and surveillance monitoring, image understanding, and motion capture. In this work we develop methods that make use of single view cameras, stereo, and range sensors.(More)
Wide Area Aerial Surveillance (WAAS) produces very large images at 1-2 fps or more. This data needs to be processed in real time to produce semantically meaningful information, then queried efficiently. We have designed and implemented a full system to detect and track vehicles, and infer activities. We address here the scalability issues, and propose(More)