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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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Real-time detection of moving objects from moving vehicles using dense stereo and optical flow

Dynamic scene perception is very important for autonomous vehicles operating around other moving vehicles and humans. Most work on real-time object tracking from moving platforms has used sparse features or assumed flat scene structures. We have recently extended a real-time, dense stereo system to include real-time, dense optical flow, enabling more comprehensive dynamic scene analysis. We describe algorithms to robustly estimate 6-DOF robot egomotion in the presence of moving objects using dense flow and dense stereo. We then use dense stereo and egomotion estimates to identity other moving objects while the robot itself is moving. We present results showing accurate egomotion estimation and detection of moving people and vehicles under general 6-DOF motion of the robot and independently moving objects. The system runs at 18.3 Hz on a 1.4 GHz Pentium M laptop, computing 160x120 disparity maps and optical flow fields, egomotion, and moving object segmentation. We believe this is a significant step toward general unconstrained dynamic scene analysis for mobile robots, as well as for improved position estimation where GPS is unavailable.

egomotion↗

Real-time detection of moving objects from moving vehicles using dense stereo and optical flow

Dynamic scene perception is very important for autonomous vehicles operating around other moving vehicles and humans. Most work on real-time object tracking from moving platforms has used sparse features or assumed flat scene structures. We have recently extended a real-time, dense stereo system to include realtime, dense optical flow, enabling more comprehensive dynamic scene analysis. We describe algorithms to robustly estimate 6-DOF robot egomotion in the presence of moving objects using dense flow and dense stereo. We then use dense stereo and egomotion estimates to identify & other moving objects while the robot itself is moving. We present results showing accurate egomotion estimation and detection of moving people and vehicles under general 6-DOF motion of the robot and independently moving objects. The system runs at 18.3 Hz on a 1.4 GHz Pentium M laptop, computing 160x120 disparity maps and optical flow fields, egomotion, and moving object segmentation. We believe this is a significant step toward general unconstrained dynamic scene analysis for mobile robots, as well as for improved position estimation where GPS is unavailable.

egomotion↗

Real-time Detection of Moving Objects from Moving Vehicles Using Dense Stereo and Optical Flow

Dynamic scene perception is very important for autonomous vehicles operating around other moving vehicles and humans. Most work on real-time object tracking from moving platforms has used sparse features or assumed flat scene structures. We have recently extended a real-time. dense stereo system to include realtime. dense optical flow, enabling more comprehensive dynamic scene analysis. We describe algorithms to robustly estimate 6-DOF robot egomotion in the presence of moving objects using dense flow and dense stereo. We then use dense stereo and egomotion estimates to identify other moving objects while the robot itself is moving. We present results showing accurate egomotion estimation and detection of moving people and vehicles under general 6DOF motion of the robot and independently moving objects. The system runs at 18.3 Hz on a 1.4 GHz Pentium M laptop. computing 160x120 disparity maps and optical flow fields, egomotion, and moving object segmentation. We believe this is a significant step toward general unconstrained dynamic scene analysis for mobile robots, as well as for improved position estimation where GPS is unavailable.

moving object detection↗

The Interaction of Focused Attention with Flow-field Sensitivity

Two studies were performed to determine whether a subject's response to naturalistic optical flow specifying egomotion would be affected by a concurrent attention task. In the first study subjects stood in a moving room in which various areas of the optical flow generated by room movement were visible. Subjects responded to room motion with strong compensatory sway when the entire room was visible. When the side walls of the room were completely obscured by stationary screens, leaving only the front wall visible, sway was significantly reduced, though it remained greater than in an eyes-closed control. In Exp. 2 subjects were presented with either the full room (large sway response) or the room with only the front wall visible (moderate response), each in combination with either a hard or easy verbal addition task. Preliminary results show that swaying in the fully visible room and in the room with only the front wall visible increased when combined with either the hard or easy tasks. These preliminary results suggest that at the least the pick-up of optical flow specifying egomotion is not affected by concurrent attentional activity.

Stoffregen, T.↗

Simple control-theoretic models of human steering activity in visually guided vehicle control

A simple control theoretic model of human steering or control activity in the lateral-directional control of vehicles such as automobiles and rotorcraft is discussed. The term 'control theoretic' is used to emphasize the fact that the model is derived from a consideration of well-known control system design principles as opposed to psychological theories regarding egomotion, etc. The model is employed to emphasize the 'closed-loop' nature of tasks involving the visually guided control of vehicles upon, or in close proximity to, the earth and to hypothesize how changes in vehicle dynamics can significantly alter the nature of the visual cues which a human might use in such tasks.

Hess, Ronald A.↗

Vision-Aided Autonomous Landing and Ingress of Micro Aerial Vehicles

Micro aerial vehicles have limited sensor suites and computational power. For reconnaissance tasks and to conserve energy, these systems need the ability to autonomously land at vantage points or enter buildings (ingress). But for autonomous navigation, information is needed to identify and guide the vehicle to the target. Vision algorithms can provide egomotion estimation and target detection using input from cameras that are easy to include in miniature systems.

Brockers, Roland↗

Visual odometry on the Mars Exploration Rovers

In this paper we describe the Visual Odometry algorithm used on the Mars Exploration Rovers, and summarize the results obtained by running this processing onboard during the first year of operations on Mars.

egomotion↗