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Most Wide Area Motion Imagery (WAMI) based trackers use motion based cueing for detecting and tracking moving objects. The results are very high false alarm rates in urban environments with tall structures due to parallax effects. This paper proposes an accurate moving object detection method using a precise orthorectification approach for ground stabilization combined with accurate multiview depth...
This paper addresses the problem of learning meaningful human action attributes from high-dimensional video sequences based on union-of-subspaces (UoS) model. The model hypothesizes that each action attribute is represented by a subspace. It puts forth an extension of existing low-rank representation (LRR), termed the clustering-aware structure-constrained low-rank representation (CS-LRR) model, for...
This report summarizes the findings of an exploratory team of the North Atlantic Treaty Organization (NATO) Information Systems Technology panel into Content-Based Analytics (CBA). The team carried out a technical review into the current status of theoretical and practical developments of methods, tools and techniques supporting joint exploitation of multimedia data sources. In particular, content-based...
The need for persistent video covering large geospatial areas using embedded camera networks and stand-off sensors has increased over the past decade. The availability of inexpensive, compact, light-weight, energy-efficient, high resolution optical sensors and associated digital image processing hardware has led to a new class of airborne surveillance platforms. Traditional tradeoffs posed between...
The current mode of image capture in remote sensing of the earth by aircraft or satellite based sensors is in digital form. The pixels correspond to localized spatial information while the quantization levels in each spectral band correspond to the quantized radiometric measurements. It is most logical to regard each image as a vector array, that is, the pixels are arranged on a rectangular grid but...
A hierarchical union-of-subspaces model is proposed for performing semi-supervised human activity summarization in large streams of video data. The union of low-dimensional subspaces model is used to learn meaningful action attributes from a collection of high-dimensional video sequences of human activities. An approach called hierarchical sparse subspace clustering (HSSC) is developed to learn this...
The diagnosis and treatment of malaria infection requires detecting the presence of the malaria parasite in the patient as well as identification of the parasite species. We present an image processing-based approach to detect parasites in microscope images of a blood smear and an ontology-based classification of the stage of the parasite for identifying the species of infection. This approach is...
The flux tensor motion flow algorithm is a versatile computer vision technique for robustly detecting moving objects in cluttered scenes. The flux tensor calculation has a high computational workload consisting of 3-D spatiotemporal filtering operations combined with 3-D weighted integration operations for estimating local averages of the flux tensor matrix trace. In order to achieve efficient real-time...
Given the statistically multiplexed stream observations of two independent and different types of traffic streams, this paper examines the problem of determining the degree of mixing. In data networks a common example of such a pair of different stream would be one conforming to the traditional Poisson model with an exponential inter-arrival distribution and the other obeying long-range dependent...
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