Segmented Tracks Research Articles

Multiple object tracking with behavior detection in crowded scenes using deep learning

Multi-object tracking (MOT) is essential for solving the majority of computer vision issues related to crowd analytics. In an MOT system designing object detection and association are the two main steps. Every frame of the video stream is examined to find the desired objects in the first step. Their trajectories are determined in the second step by comparing the detected objects in the current frame to those in the previous frame. Less missing detections are made possible by an object detection system with high accuracy, which results in fewer segmented tracks. We propose a new deep learning-based model for improving the performance of object detection and object tracking in this research. First, object detection is performed by using the adaptive Mask-RCNN model. After that, the ResNet-50 model is used to extract more reliable and significant features of the objects. Then the effective adaptive feature channel selection method is employed for selecting feature channels to determine the final response map. Finally, an adaptive combination kernel correlation filter is used for multiple object tracking. Extensive experiments were conducted on large object-tracking databases like MOT-20 and KITTI-MOTS. According to the experimental results, the proposed tracker performs better than other cutting-edge trackers when faced with various problems. The experimental simulation is carried out in python. The overall success rate and precision of the proposed algorithm are 95.36% and 93.27%.

Personalized biomechanical tongue models based on diffusion-weighted MRI and validated using optical tracking of range of motion

For advanced tongue cancer, the choice between surgery and organ-sparing treatment is often dependent on the expected loss of tongue functionality after treatment. Biomechanical models might assist in this choice by simulating the post-treatment function loss. However, this function loss varies between patients and should, therefore, be predicted for each patient individually. In the present study, the goal was to better predict the postoperative range of motion (ROM) of the tongue by personalizing biomechanical models using diffusion-weighted MRI and constrained spherical deconvolution reconstructions of tongue muscle architecture. Diffusion-weighted MRI scans of ten healthy volunteers were obtained to reconstruct their tongue musculature, which were subsequently registered to a previously described population average or atlas. Using the displacement fields obtained from the registration, the segmented muscle fiber tracks from the atlas were morphed back to create personalized muscle fiber tracks. Finite element models were created from the fiber tracks of the atlas and those of the individual tongues. Via inverse simulation of a protruding, downward, left and right movement, the ROM of the tongue was predicted. This prediction was compared to the ROM measured with a 3D camera. It was demonstrated that biomechanical models with personalized muscles bundles are better in approaching the measured ROM than a generic model. However, to achieve this result a correction factor was needed to compensate for the small magnitude of motion of the model. Future versions of these models may have the potential to improve the estimation of function loss after treatment for advanced tongue cancer.

Modeling for Segmented Tracks Planning of Roadway-Powered Electric Vehicles

Electric vehicle has aroused peoples concern with soaring energy crisis and environmental degradation. However, it has not been widely used due to some drawbacks, such as the short driving range, long charging time, frequent charging requirements and high price. In order to solve these problems, the roadway-powered electric vehicles (RPEVs) based on an inductive power transfer (IPT) has been proposed. In the segmented RPEVs system, efficiency and annual cost are affected by the track distance, tracks interval, number of tracks and installed capacity of each track, etc. Aiming to such problem, the nonlinear programming (NLP) model for segmented tracks planning of RPEVs system is studied in this paper. Meanwhile, the relationship between the system efficiency and the number of loads is analyzed as a cogent argument to the application of segmented tracks.

Segmented Tracks Planning of Roadway-Powered System for Electric Vehicles using Improved Particle Swarm Optimization

Segmented Tracks Planning of Roadway-Powered System for Electric Vehicles using Improved Particle Swarm Optimization

Performance measurements of a tracked vehicle system

To improve crossing ability, the most important performance factor for tracked vehicle systems operating on low-bearing capacity peats, and to minimize income losses that result from downtime and maintenance costs, a vehicle was designed in order to adapt to operating condition changes. This article describes the mobile performance of a novel vehicle with segmented rubber tracks on a low-bearing capacity peat. At an equivalent travelling speed, the novel vehicle’s tractive performance in a variable operating environment caused by changes in terrain cohesiveness and hydrodynamic responses was superior to that of the previous model. The new vehicle, which could be operated on the Sepang peat, showed a tractive effort of 42.2% of the gross vehicle weight in field experiments; the recommended minimum tractive effort is between 30 and 36% of the gross vehicle weight.

Efficient detection and tracking of moving objects in geo-coordinates

We present a system to detect and track moving objects from an airborne platform. Given a global map, such as a satellite image, our approach can locate and track the targets in geo-coordinates, namely longitude and latitude obtained from geo-registration. A motion model in geo-coordinates is more physically meaningful than the one in image coordinates. We propose to use a two-step geo-registration approach to stitch images acquired by satellite and UAV cameras. Mutual information is used to find correspondences between these two very different modalities. After motion segmentation and geo-registration, tracking is performed in a hierarchical manner: at the temporally local level, moving image blobs extracted by motion segmentation are associated into tracklets; at the global level, tracklets are linked by their appearance and spatio-temporal consistency on the global map. To achieve efficient time performance, graphics processing unit techniques are applied in the geo-registration and motion detection modules, which are the bottleneck of the whole system. Experiments show that our method can efficiently deal with long term occlusion and segmented tracks even when targets fall out the field of view.

A routing algorithm for row-based FPGAs

A row-based Field Programmable Gate Array (FPGA) consists of rows of identical processing modules separated by segmented tracks that are used for routing nets between specified module pins. The problem of finding a feasible routing of a given set of nets onto a set of segmented tracks is NP-complete. We present an enumeration algorithm for the problem that uses matching arguments to improve the time complexity while requiring polynomial space. The algorithm serves as the basis of powerful practical heuristics and its additional advantage is that it is directly parallelizable.

Main component of the error of wheelwise weighing of locomotives

1. In the case of wheelwise weighing of locomotives, the redistribution of wheel loads as a consequence of their different height on the scales can introduce substantial errors into the measurement results. 2. For these errors to have an acceptable value (about 0.5%), the design of locomotive scales should provide such placement of all wheels of the locomotive being weighed for which their points of contact with the load-receiving devices are in one horizontal plane at the time of taking the readings (with a deviation of no more than 0.2–0.3 mm), which is achieved most simply in scales with stationary weight-measuring instruments and segmented tracks.