Rectangling irregular videos by optimal spatio-temporal warping

Image and video processing based on geometric principles typically changes the rectangular shape of video frames to an irregular shape. This paper presents a warping based approach for rectangling such irregular frame boundaries in space and time, i.e., making them rectangular again. To reduce geometric distortion in the rectangling process, we employ content-preserving deformation of a mesh grid with line structures as constraints to warp the frames. To conform to the original inter-frame motion, we keep feature trajectory distribution as constraints during motion compensation to ensure stability after warping the frames. Such spatially and temporally optimized warps enable the output of regular rectangular boundaries for the video frames with low geometric distortion and jitter. Our experiments demonstrate that our approach can generate plausible video rectangling results in a variety of applications.

UNCOVERING THE AGGREGATION PATTERN OF GPS TRAJECTORY BASED ON SPATIOTEMPORAL CLUSTERING AND 3D VISUALIZATION

Constrained by road network structure, travel choice and city function zoning, GPS trajectory data exhibits significant spatiotemporal correlation. Unveiling the clustering and distribution patterns of GPS trajectory can help to better understand the travel behaviour as well as the corresponding spatial and temporal characteristics. This paper proposes an approach to identify and visualize the aggregation pattern from GPS trajectory data. Firstly, slow feature trajectory sequences are extracted from raw taxi trajectory data. Together with taxi states information, these sequences are processed as shorter length tracks for faster discovery of cluster similarity. Thereafter, the temporal and spatial similarity and dissimilarity metrics between the trajectories are established, and the temporal and spatial distances between the trajectories are defined to form a space-time cylinder model. Next, based on the idea of density clustering, the DBSCAN spatiotemporal expansion of trajectory data is proposed. Feature trajectory sequences are then clustered into groups with high similarity. Finally, for a more intuitive understanding of the trajectory aggregate distribution, time dimension info of each point in the sequences is used as Z axis, thus the sequences are stretched on the map in different colour for 3D visualization. The proposed method is validated by a case study of taxi trajectory data analysis in Wuhan City, China.

Path planning for visual servoing with search algorithm

To solve the visual servoing tasks in complex environment, a path planning method based on improved rapidly exploring random trees algorithm is proposed. First, the improved rapidly exploring random trees planning method is adopted, which keeps the observed feature points in the field of view. The start node and the desired node are initialized as roots of multi-trees which grow harmoniously to plan path of the robot. Then, the planned path is used to project the three-dimensional target feature points into the image space and obtain the feature trajectory for the image-based visual servoing controller. Finally, the feature trajectory is tracked by the image-based visual servoing controller. The proposed visual servoing design method takes field of view constraints, camera retreat problem, and obstacle avoidance into consideration, which can significantly improve the ability of the robotic manipulator, especially in the narrow space. Simulation and experiment on 6-degree-of-freedom robot are conducted. The results present the effectiveness of the proposed algorithm.

Real-Time Video Stabilization Based on Smoothing Feature Trajectories

In this paper, a real-time video stabilization algorithm based on smoothing feature trajectories is proposed. For each input frame, our approach generates multiple feature trajectories by performing inter-frame template match and optical flow. A Kalman filter is then performed to smooth these feature trajectories. Finally, at the stage of image composition, the motion consistency of the feature trajectory is considered for achieving a visually plausible stabilized video. The proposed method can offer real-time video stabilization and its removed the delays for caching coming images. Experiments show that our approach can offer real-time stabilizing for videos with various complicated scenes.