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This paper describes a computer vision approach to automated rapid-throughput taxonomic identification of stonefly larvae. The long-term objective of this research is to develop a cost-effective method for environmental monitoring based on automated identification of indicator species. Recognition of stonefly larvae is challenging because they are highly(More)
This paper presents a new structure-based interest region detector called Principal Curvature-Based Regions (PCBR) which we use for object class recognition. The PCBR interest operator detects stable watershed regions within the multi-scale principal curvature image. To detect robust watershed regions, we " clean " a principal curvature image by combining a(More)
This paper describes a fully automated stonefly-larvae classification system using a local features approach. It compares the three region detectors employed by the system: the Hessian-affine detector, the Kadir entropy detector and a new detector we have developed called the principal curvature based region detector (PCBR). It introduces a concatenated(More)
This paper proposes a new generic object recognition system based on multi-scale affine-invariant image regions. Image segments are obtained by a watershed transform of the principal curvature of a contrast enhanced image. Each region is described by an intensity-based statistical descriptor and a PCA-SIFT descriptor. The spatial relations between regions(More)
Automated extraction of semantic information from a network of sensors for cognitive analysis and human-like reasoning is a desired capability in future ground surveillance systems. We tackle the problem of complex decision making under uncertainty in network information environment , where lack of effective visual processing tools, incomplete domain(More)
Visual dictionaries have been successfully applied to " bags-of-points " image representations for generic object recognition. Usually the choice of low-level interest region detector and region descriptor (channel) has significant impact on the performance of visual dictionaries. In this paper, we propose a discrimina-tive evaluation method-Maximum Mutual(More)
This paper presents a fast forensic video events analysis and retrieval system in a geospatial framework. Starting from tracking targets and analyzing video streams from distributed camera networks, the system generates video tracking metadata for each video, maps and fuses them in a uniform geospatial coordinate. The combined metadata is saved into spatial(More)