Dataset Information

Efficient multiple object tracking using mutually repulsive active membranes.

ABSTRACT: Studies of social and group behavior in interacting organisms require high-throughput analysis of the motion of a large number of individual subjects. Computer vision techniques offer solutions to specific tracking problems, and allow automated and efficient tracking with minimal human intervention. In this work, we adopt the open active contour model to track the trajectories of moving objects at high density. We add repulsive interactions between open contours to the original model, treat the trajectories as an extrusion in the temporal dimension, and show applications to two tracking problems. The walking behavior of Drosophila is studied at different population density and gender composition. We demonstrate that individual male flies have distinct walking signatures, and that the social interaction between flies in a mixed gender arena is gender specific. We also apply our model to studies of trajectories of gliding Myxococcus xanthus bacteria at high density. We examine the individual gliding behavioral statistics in terms of the gliding speed distribution. Using these two examples at very distinctive spatial scales, we illustrate the use of our algorithm on tracking both short rigid bodies (Drosophila) and long flexible objects (Myxococcus xanthus). Our repulsive active membrane model reaches error rates better than 5 x 10(-6) per fly per second for Drosophila tracking and comparable results for Myxococcus xanthus.

SUBMITTER: Deng Y

PROVIDER: S-EPMC3683037 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Publications

Efficient multiple object tracking using mutually repulsive active membranes.

Deng Yi Y Coen Philip P Sun Mingzhai M Shaevitz Joshua W JW

PloS one 20130614 6

Studies of social and group behavior in interacting organisms require high-throughput analysis of the motion of a large number of individual subjects. Computer vision techniques offer solutions to specific tracking problems, and allow automated and efficient tracking with minimal human intervention. In this work, we adopt the open active contour model to track the trajectories of moving objects at high density. We add repulsive interactions between open contours to the original model, treat the ...[more]

PMID: 23799046

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Project description:A mirror-based active system capable of changing the view's direction of a pre-existing fixed camera is presented. The aim of this research work is to extend the perceptual tracking capabilities of an underwater robot without altering its structure. The ability to control the view's direction allows the robot to explore its entire surroundings without any actual displacement, which can be useful for more effective motion planning and for different navigation strategies, such as object tracking and/or obstacle evasion, which are of great importance for natural preservation in environments as complex and fragile as coral reefs. Active vision systems based on mirrors had been used mainly in terrestrial platforms to capture the motion of fast projectiles using high-speed cameras of considerable size and weight, but they had not been used on underwater platforms. In this sense, our approach incorporates a lightweight design adapted to an underwater robot using affordable and easy-access technology (i.e., 3D printing). Our active system consists of two arranged mirrors, one of which remains static in front of the robot's camera, while the orientation of the second mirror is controlled by two servomotors. Object tracking is performed by using only the pixels contained on the homography of a defined area in the active mirror. HSV color space is used to reduce lighting change effects. Since color and geometry information of the tracking object are previously known, a window filter is applied over the H-channel for color blobs detection, then, noise is filtered and the object's centroid is estimated. If the object is lost, a Kalman filter is applied to predict its position. Finally, with this information, an image PD controller computes the servomotor articular values. We have carried out experiments in real environments, testing our active vision system in an object-tracking application where an artificial object is manually displaced on the periphery of the robot and the mirror system is automatically reconfigured to keep such object focused by the camera, having satisfactory results in real time for detecting objects of low complexity and in poor lighting conditions.

Dataset Information

Efficient multiple object tracking using mutually repulsive active membranes.

Publications

Efficient multiple object tracking using mutually repulsive active membranes.

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