The CMS Silicon Strip Tracker

The CMS strip tracker is the first large scale tracker entirely based on silicon detectors technology. It consists of 198 m^2 of detector sensitive area instrumenting the inner region of the experiment with a pseudo-rapidity coverage of eta <2.5. This instrument, together with a silicon pixel system, is expected to perform robust tracking and detailed vertex reconstruction while embedded in the LHC high radiation and high luminosity environment. The project is in a well advanced construction phase: the detector module production is completed, the integration of the single components into large sub-detector units is underway and the full tracker commissioning is about to start. In this paper, after a description of the tracker layout, a detector modules production overview and a summary of the integration procedures for the inner barrel part of the tracker will be reported

Realtime tracking and grasping of a moving object from range video

In this paper we present an automated system that is able to track and grasp a moving object within the workspace of a manipulator using range images acquired with a Microsoft Kinect sensor. Realtime tracking is achieved by a geometric particle filter on the affine group. Based on the tracked output, the pose of a 7-DoF WAM robotic arm is continuously updated using dynamic motor primitives until a distance measure between the tracked object and the gripper mounted on the arm is below a threshold. Then, it closes its three fingers and grasps the object. The tracker works in real-time and is robust to noise and partial occlusions. Using only the depth data makes our tracker independent of texture which is one of the key design goals in our approach. An experimental evaluation is provided along with a comparison of the proposed tracker with state-of-the-art approaches, including the OpenNI-tracker. The developed system is integrated with ROS and made available as part of IRI's ROS stack.Peer ReviewedPostprint (author’s final draft

Object Tracking in Video with Part-Based Tracking by Feature Sampling

Visual tracking of arbitrary objects is an active research topic in computer vision, with applications across multiple disciplines including video surveillance, activity analysis, robot vision, and human computer interface. Despite great progress having been made in object tracking in recent years, it still remains a challenge to design trackers that can deal with difficult tracking scenarios, such as camera motion, object motion change, occlusion, illumination changes, and object deformation. A promising way of tackling these types of problems is to use a part-based method; one which models and tracks small regions of the object and estimates the location of the object based on the tracked part's positions. These approaches typically model parts of objects with histograms of various hand-crafted features extracted from the region in which the part is located. However, it is unclear how such relatively homogeneous regions should be represented to form an effective part-based tracker. In this thesis we present a part-based tracker that includes a model for object parts that is designed to empirically characterise the underlying colour distribution of an image region, representing it by pairs of randomly selected colour features and counts of how many pixels are similar to each feature. This novel feature representation is used to find probable locations for the part in future frames via a Bhattacharyya Distance-based metric, which is modified to prefer higher quality matches. Sets of candidate patch locations are generated by randomly generating non-shearing affine transformations of the part's previous locations and locally optimising the most likely sets of parts to allow for small intra-frame object deformations. We also present a study of model initialisation in online, model-free tracking and evaluate several techniques for selecting the regions of an image, given a target bounding box most likely to contain an object. The strengths and limitations of the combined tracker are evaluated on the VOT2016 and VOT2018 datasets using their evaluation protocol, which also allows an extensive evaluation of parameter robustness. The presented tracker is ranked first among part-based trackers on the VOT2018 dataset and is particularly robust to changes in object and camera motion, as well as object size changes

Evaluation of trackers for Pan-Tilt-Zoom Scenarios

Tracking with a Pan-Tilt-Zoom (PTZ) camera has been a research topic in computer vision for many years. Compared to tracking with a still camera, the images captured with a PTZ camera are highly dynamic in nature because the camera can perform large motion resulting in quickly changing capture conditions. Furthermore, tracking with a PTZ camera involves camera control to position the camera on the target. For successful tracking and camera control, the tracker must be fast enough, or has to be able to predict accurately the next position of the target. Therefore, standard benchmarks do not allow to assess properly the quality of a tracker for the PTZ scenario. In this work, we use a virtual PTZ framework to evaluate different tracking algorithms and compare their performances. We also extend the framework to add target position prediction for the next frame, accounting for camera motion and processing delays. By doing this, we can assess if predicting can make long-term tracking more robust as it may help slower algorithms for keeping the target in the field of view of the camera. Results confirm that both speed and robustness are required for tracking under the PTZ scenario.Comment: 6 pages, 2 figures, International Conference on Pattern Recognition and Artificial Intelligence 201

Design and analysis of a low-profile two-axis solar tracker with hybridized control

The adoption of solar power technologies throughout the world is increasing rapidly. Solar trackers are a necessary component in Concentrated Solar Power (CSP) applications and have also shown up to 46% per annum energy increase in photovoltaic (PV) panels when compared with fixed mounted panels. To resist wind forces, trackers typically incorporate heavy structural components and reinforced concrete foundations. Thus, the manufacture and installation of trackers is costly due to their size, weight, and careful consideration of geological conditions. This work presents a new solar tracker design for use with concentrating solar power and photovoltaic panels. The tracker is comprised of two coplanar perpendicular linear actuators and one linkage arm that can track the sun in two axes. A hybrid control strategy combines time and location based solar position estimates, with a two-axis misalignment sensor for a robust control strategy. Part cost is lowered by the low profile tracker geometry by allowing lighter structural and actuation components to combat gusty conditions, and installation costs are reduced by the wide footprint of the system, mitigating the need for deep foundations. A tracker prototype is built and tested for functionality and tracking accuracy. Testing shows an average mechanical pointing hysteresis of 0.05 [degrees]. The tracker is outfitted with a parabolic mirror and blackbody receiving cavity, and in full sun reaches a steady-state temperature of 670 [degrees] C