Binaries among low-mass stars in nearby young moving groups

The solar galactic neighbourhood contains a number of young co-moving associations of stars (so-called `young moving groups') with ages of ~10--150 Myr, which are prime targets for a range of scientific studies, including direct imaging planet searches. The late-type stellar population of such groups still remain in their pre-main sequence phase, and are thus well suited for purposes such as isochronal dating. Close binaries are particularly useful in this regard, since they allow for a model-independent dynamical mass determination. Here we present a dedicated effort to identify new close binaries in nearby young moving groups, through high-resolution imaging with the AstraLux Sur Lucky Imaging camera. We surveyed 181 targets, resulting in the detection of 61 companions or candidates, of which 38 are new discoveries. An interesting example of such a case is 2MASS J00302572-6236015 AB, which is a high-probability member of the Tucana-Horologium moving group, and has an estimated orbital period of less than 10 years. Among the previously known objects is a serendipitous detection of the deuterium burning boundary circumbinary companion 2MASS J01033563-5515561 (AB)b in the z'-band, thereby extending the spectral coverage for this object down to near-visible wavelengths.Comment: 12 pages, 3 figures, accepted for publication in A&

Dynamic 3D Urban Scene Modeling Using Multiple Pushbroom Mosaics

In this paper, a unified, segmentation-based approach is proposed to deal with both stereo reconstruction and moving objects detection problems using multiple stereo mosaics. Each set of parallel-perspective (pushbroom) stereo mosaics is generated from a video sequence captured by a single video camera. First a colorsegmentation approach is used to extract the so-called natural matching primitives from a reference view of a pair of stereo mosaics to facilitate both 3D reconstruction of textureless urban scenes and man-made moving targets (e.g. vehicles). Multiple pairs of stereo mosaics are used to improve the accuracy and robustness in 3D recovery and occlusion handling. Moving targets are detected by inspecting their 3D anomalies, either violating the epipolar geometry of the pushbroom stereo or exhibiting abnormal 3D structure. Experimental results on both simulated and real video sequences are provided to show the effectiveness of our approach. 1

TRADE: Object Tracking with 3D Trajectory and Ground Depth Estimates for UAVs

We propose TRADE for robust tracking and 3D localization of a moving target in cluttered environments, from UAVs equipped with a single camera. Ultimately TRADE enables 3d-aware target following. Tracking-by-detection approaches are vulnerable to target switching, especially between similar objects. Thus, TRADE predicts and incorporates the target 3D trajectory to select the right target from the tracker's response map. Unlike static environments, depth estimation of a moving target from a single camera is a ill-posed problem. Therefore we propose a novel 3D localization method for ground targets on complex terrain. It reasons about scene geometry by combining ground plane segmentation, depth-from-motion and single-image depth estimation. The benefits of using TRADE are demonstrated as tracking robustness and depth accuracy on several dynamic scenes simulated in this work. Additionally, we demonstrate autonomous target following using a thermal camera by running TRADE on a quadcopter's board computer

Coil Gun Turret Control Using A Camera

ABSTRACT --- A conventional weapon usually by pointing to the target aimed by using hands. It is considered less effective and efficient in terms of military service because of spending lots of time to chase the target. So needed a tool to move the weapon automatically. This final project present about object tracking in a weapon and it’s turret, that will be controlled by camera. The camera is used to detect moving targets based on a particular color. In a image sequence consisting of many different objects, accompanied by a different background, this system will be able to distinguish between the target or not. Camera detection is done by taking moving images with color composition that has been determined. Then, The image resolution is resized of the smallest of camera’s resolutions, that is 320x240. Smaller image size are intended for the system’s working to be faster. Capturing image process is use segmentation object process in digital image processing which aims to separate the object region with background. The weapon that will be used, have two degrees of freedom. Maximum 360 degrees rotation in x axis, and maximum 90 degrees in y axis. Both of them using brushed DC motor. At the direction of the y- axis motion required a gear for transmitting power between motor shaft and the shaft, so the shaft is not directly connected to the motor and no distortion. Turret have been designed had four buffers as a solid foundation to bear the entire load. Communication between the camera and weapons carried out by using the cable. Turret will be controlled using the PD control which is expected to reach a position with a quick reference. Key Words: Object tracking, Digital Image Processing, Image sequence, PD (Proposional Deravative) Contro

Automatic aerial target detection and tracking system in airborne FLIR images based on efficient target trajectory filtering

Common strategies for detection and tracking of aerial moving targets in airborne Forward-Looking Infrared (FLIR) images offer accurate results in images composed by a non-textured sky. However, when cloud and earth regions appear in the image sequence, those strategies result in an over-detection that increases very significantly the false alarm rate. Besides, the airborne camera induces a global motion in the image sequence that complicates even more detection and tracking tasks. In this work, an automatic detection and tracking system with an innovative and efficient target trajectory filtering is presented. It robustly compensates the global motion to accurately detect and track potential aerial targets. Their trajectories are analyzed by a curve fitting technique to reliably validate real targets. This strategy allows to filter false targets with stationary or erratic trajectories. The proposed system makes special emphasis in the use of low complexity video analysis techniques to achieve real-time operation. Experimental results using real FLIR sequences show a dramatic reduction of the false alarm rate, while maintaining the detection rate

Binaries among low-mass stars in nearby young moving groups

The solar galactic neighborhood contains a number of young co-moving associations of stars (known as young moving groups) with ages of ~10–150 Myr, which are prime targets for a range of scientific studies, including direct imaging planet searches. The late-type stellar populations of such groups still remain in their pre-main sequence phase, and are thus well suited for purposes such as isochronal dating. Close binaries are particularly useful in this regard since they allow for a model-independent dynamical mass determination. Here we present a dedicated effort to identify new close binaries in nearby young moving groups, through high-resolution imaging with the AstraLux Sur Lucky Imaging camera. We surveyed 181 targets, resulting in the detection of 61 companions or candidates, of which 38 are new discoveries. An interesting example of such a case is 2MASS J00302572-6236015 AB, which is a high-probability member of the Tucana-Horologium moving group, and has an estimated orbital period of less than 10 yr. Among the previously known objects is a serendipitous detection of the deuterium burning boundary circumbinary companion 2MASS J01033563-5515561 (AB)b in the z′ band, thereby extending the spectral coverage for this object down to near-visible wavelengths

Vision-based detection and tracking of moving target in video surveillance

In this paper a real-time detection and tracking of moving targets is presented. The scheme involved four phases. Phase one: Object segmentation which used to identify the foreground objects from the background by using background subtraction based on temporal differencing and a rolling-average background model. Phase two: Object recognition used to identify the foreground objects that should be tracked by using simple blob detection. Phase three: Object representation which takes the outcome from phase two. It computes the representation of each recognized object to be tracked. Phase 4: Object tracking that used Kalman filter. The results show that the tracking system is capable of target shape recovery and therefore it can successfully track targets with varying distance from camera or while the camera is zoomin

Aerial moving target detection based on motion vector field analysis

An efficient automatic detection strategy for aerial moving targets in airborne forward-looking infrared (FLIR) imagery is presented in this paper. Airborne cameras induce a global motion over all objects in the image, that invalidates motion-based segmentation techniques for static cameras. To overcome this drawback, previous works compensate the camera ego-motion. However, this approach is too much dependent on the quality of the ego-motion compensation, tending towards an over-detection. In this work, the proposed strategy estimates a robust motion vector field, free of erroneous vectors. Motion vectors are classified into different independent moving objects, corresponding to background objects and aerial targets. The aerial targets are directly segmented using their associated motion vectors. This detection strategy has a low computational cost, since no compensation process or motion-based technique needs to be applied. Excellent results have been obtained over real FLIR sequences