Existing methods for video scene analysis are primarily concerned with learning motion patterns or models for anomaly detection. We present a novel form of video scene analysis where scene element categories such as roads, parking areas, sidewalks and entrances, can be segmented and categorized based on the behaviors of moving objects in and around them. We view the problem from the perspective of categorical object recognition, and present an approach for unsupervised learning of functional scene element categories. Our approach identifies functional regions with similar behaviors in the same scene and/or across scenes, by clustering histograms based on a trajectory-level, behavioral codebook. Experiments are conducted on two outdoor webcam video scenes with low frame rates and poor quality. Unsupervised classification results are presented for each scene independently, and also jointly where models learned on one scene are applied to the other.
Objective-Many image-guided surgery applications require tracking devices as part of their core functionality. The Image-Guided Surgery Toolkit (IGSTK) was designed and developed to interface tracking devices with software applications incorporating medical images.Methods-IGSTK was designed as an open source C++ library that provides the basic components needed for fast prototyping and development of image-guided surgery applications. This library follows a component-based architecture with several components designed for specific sets of imageguided surgery functions. At the core of the toolkit is the tracker component that handles communication between a control computer and navigation device to gather pose measurements of surgical instruments present in the surgical scene. The representations of the tracked instruments are superimposed on anatomical images to provide visual feedback to the clinician during surgical procedures.Results-The initial version of the IGSTK toolkit has been released in the public domain and several trackers are supported. The toolkit and related information are available at www.igstk.org.Conclusion-With the increased popularity of minimally invasive procedures in health care, several tracking devices have been developed for medical applications. Designing and implementing high-quality and safe software to handle these different types of trackers in a common framework is a challenging task. It requires establishing key software design principles that emphasize abstraction, extensibility, reusability, fault-tolerance, and portability. IGSTK is an open source library that satisfies these needs for the image-guided surgery community.
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