This paper presents a technique for trajectory classification with applications to dynamic free-air hand gesture recognition. Such gestures are unencumbered and drawn in free air. Our approach is an extension to the longest common subsequence (LCS) classification algorithm. A learning preprocessing stage is performed to create a probabilistic 2-D template for each gesture, which allows taking into account different trajectory distortions with different probabilities. The modified LCS, termed the most probable LCS (MPLCS), is developed to measure the similarity between the probabilistic template and the hand gesture sample. The final decision is based on the length and probability of the extracted subsequence. Validation tests using a cohort of gesture digits from video-based capture show that the approach is promising with a recognition rate of more than 98 % for video stream preisolated digits. The MPLCS algorithm can be integrated into a gesture recognition interface to facilitate gesture character input. This can greatly enhance the usability of such interfaces.
The use of doctor-computer interaction devices in the operation room (OR) requires new modalities that support medical imaging manipulation while allowing doctors' hands to remain sterile, supporting their focus of attention, and providing fast response times. This paper presents "Gestix," a vision-based hand gesture capture and recognition system that interprets in real-time the user's gestures for navigation and manipulation of images in an electronic medical record (EMR) database. Navigation and other gestures are translated to commands based on their temporal trajectories, through video capture. "Gestix" was tested during a brain biopsy procedure. In the in vivo experiment, this interface prevented the surgeon's focus shift and change of location while achieving a rapid intuitive reaction and easy interaction. Data from two usability tests provide insights and implications regarding human-computer interaction based on nonverbal conversational modalities.
The use of doctor-computer interaction devices in the operation room (OR) requires new modalities that support medical imaging manipulation while allowing doctors' hands to remain sterile, supporting their focus of attention, and providing fast response times. This paper presents "Gestix," a vision-based hand gesture capture and recognition system that interprets in real-time the user's gestures for navigation and manipulation of images in an electronic medical record (EMR) database. Navigation and other gestures are translated to commands based on their temporal trajectories, through video capture. "Gestix" was tested during a brain biopsy procedure. In the in vivo experiment, this interface prevented the surgeon's focus shift and change of location while achieving a rapid intuitive reaction and easy interaction. Data from two usability tests provide insights and implications regarding human-computer interaction based on nonverbal conversational modalities.
Automated harvesting requires accurate detection and recognition of the fruit within a tree canopy in real-time in uncontrolled environments. However, occlusion, variable illumination, variable appearance and texture make this task a complex challenge. Our research discusses the development of a machine vision system, capable of recognizing occluded green apples within a tree canopy. This involves the detection of ''green'' apples within scenes of ''green leaves'', shadow patterns, branches and other objects found in natural tree canopies. The system uses both thermal infra-red and color image modalities in order to achieve improved performance. Maximization of mutual information is used to find the optimal registration parameters between images from the two modalities. We use two approaches for apple detection based on low and high-level visual features. High-level features are global attributes captured by image processing operations, while low-level features are strong responses to primitive parts-based filters (such as Haar wavelets). These features are then applied separately to color and thermal infra-red images to detect apples from the background. These two approaches are compared and it is shown that the lowlevel feature-based approach is superior (74% recognition accuracy) over the high-level visual feature approach (53.16% recognition accuracy). Finally, a voting scheme is used to improve the detection results, which drops the false alarms with little effect on the recognition rate. The resulting classifiers acting independently can partially recognize the on-tree apples, however, when combined the recognition accuracy is increased.
This paper begins with a brief review of the operational aspects of bus scheduling at Egged (The Israel National Bus Carrier), and their experience with an optimal bus scheduling algorithm. Due to the limitations of this algorithm, Egged Management has decided it is still not justified to replace the manually and currently used planning procedures (comprised of 60 schedulers using Gantt charts). Consequently, an approximate procedure incorporating a man/computer interface was requested which would allow the inclusion of practical considerations that experienced schedulers may wish to introduce in the schedule. Due to its visual nature, the deficit function was selected as a natural tool to form the basis of such a man-machine interactive scheduling procedure. A deficit function defines the net number of departures required at each terminal up to and including time t. According to the well-known fleet size formula, the minimum number of vehicles required to service a multiterminal fixed schedule of trips is equal to the sum of the maximal deficits at all terminals. As deficit function theory stops at a fixed schedule of trips, it was necessary to develop procedures to (1) primarily determine when and where to insert deadheading trips, and (2) secondarily include such considerations as garage limitations, inclusion of refueling trips, and driver limitations. The final algorithm is capable of generating schedules automatically in a purely computer mode. In an interactive mode it allows the user to select one of several computer suggested improvements or to interject his own suggestions and immediately see the effects on the final schedule through observation of the deficit functions on a CRT or computer generated output.
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