17,012 research outputs found
Under vehicle perception for high level safety measures using a catadioptric camera system
In recent years, under vehicle surveillance and the classification of the vehicles become an indispensable task that must be achieved for security measures in certain areas such as shopping centers, government buildings, army camps etc. The main challenge to achieve this task is to monitor the under
frames of the means of transportations. In this paper, we present a novel solution to achieve this aim. Our solution consists of three main parts: monitoring, detection and classification. In the first part we design a new catadioptric camera system in which the perspective camera points downwards to the catadioptric mirror mounted to the body of a mobile robot. Thanks to the
catadioptric mirror the scenes against the camera optical axis direction can be viewed. In the second part we use speeded up robust features (SURF) in an object recognition algorithm. Fast appearance based mapping algorithm (FAB-MAP) is exploited for the classification of the means of transportations in the third
part. Proposed technique is implemented in a laboratory environment
Human Perambulation as a Self Calibrating Biometric
This paper introduces a novel method of single camera gait reconstruction which is independent of the walking direction and of the camera parameters. Recognizing people by gait has unique advantages with respect to other biometric techniques: the identification of the walking subject is completely unobtrusive and the identification can be achieved at distance. Recently much research has been conducted into the recognition of frontoparallel gait. The proposed method relies on the very nature of walking to achieve the independence from walking direction. Three major assumptions have been done: human gait is cyclic; the distances between the bone joints are invariant during the execution of the movement; and the articulated leg motion is approximately planar, since almost all of the perceived motion is contained within a single limb swing plane. The method has been tested on several subjects walking freely along six different directions in a small enclosed area. The results show that recognition can be achieved without calibration and without dependence on view direction. The obtained results are particularly encouraging for future system development and for its application in real surveillance scenarios
Reproducible Evaluation of Pan-Tilt-Zoom Tracking
Tracking with a Pan-Tilt-Zoom (PTZ) camera has been a research topic in
computer vision for many years. However, it is very difficult to assess the
progress that has been made on this topic because there is no standard
evaluation methodology. The difficulty in evaluating PTZ tracking algorithms
arises from their dynamic nature. In contrast to other forms of tracking, PTZ
tracking involves both locating the target in the image and controlling the
motors of the camera to aim it so that the target stays in its field of view.
This type of tracking can only be performed online. In this paper, we propose a
new evaluation framework based on a virtual PTZ camera. With this framework,
tracking scenarios do not change for each experiment and we are able to
replicate online PTZ camera control and behavior including camera positioning
delays, tracker processing delays, and numerical zoom. We tested our evaluation
framework with the Camshift tracker to show its viability and to establish
baseline results.Comment: This is an extended version of the 2015 ICIP paper "Reproducible
Evaluation of Pan-Tilt-Zoom Tracking
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