360VOTS: Visual Object Tracking and Segmentation in Omnidirectional Videos

Visual object tracking and segmentation in omnidirectional videos are challenging due to the wide field-of-view and large spherical distortion brought by 360{\deg} images. To alleviate these problems, we introduce a novel representation, extended bounding field-of-view (eBFoV), for target localization and use it as the foundation of a general 360 tracking framework which is applicable for both omnidirectional visual object tracking and segmentation tasks. Building upon our previous work on omnidirectional visual object tracking (360VOT), we propose a comprehensive dataset and benchmark that incorporates a new component called omnidirectional video object segmentation (360VOS). The 360VOS dataset includes 290 sequences accompanied by dense pixel-wise masks and covers a broader range of target categories. To support both the development and evaluation of algorithms in this domain, we divide the dataset into a training subset with 170 sequences and a testing subset with 120 sequences. Furthermore, we tailor evaluation metrics for both omnidirectional tracking and segmentation to ensure rigorous assessment. Through extensive experiments, we benchmark state-of-the-art approaches and demonstrate the effectiveness of our proposed 360 tracking framework and training dataset. Homepage: https://360vots.hkustvgd.com

The Influence of Workplace Friendship on Organizational Citizenship Behavior from the Perspective of Human Resource Management: The Regulating Effect of Workplace Social Self-efficacy

With&nbsp;the&nbsp;continuous enrichment&nbsp;of&nbsp;workplace&nbsp;situation research,&nbsp;workplace&nbsp;interpersonal relationship is gradually favored by&nbsp;management&nbsp;science and psychology. As a unique embodiment&nbsp;of&nbsp;workplace&nbsp;interpersonal relationship,&nbsp;workplace&nbsp;friendship&nbsp;naturally becomes a research hotspot in&nbsp;the&nbsp;field&nbsp;of&nbsp;organization&nbsp;management. This study is based&nbsp;on&nbsp;the&nbsp;conservation&nbsp;of&nbsp;resource&nbsp;theory, and introduced relational energy as an agent and&nbsp;the&nbsp;sense&nbsp;of&nbsp;workplace&nbsp;social&nbsp;self-efficacy as a&nbsp;regulator, so as to explore&nbsp;the&nbsp;influence&nbsp;of&nbsp;workplace&nbsp;friendship&nbsp;on&nbsp;organizational&nbsp;citizenship&nbsp;behavior. After analyzing&nbsp;the&nbsp;data&nbsp;of&nbsp;409 workers,&nbsp;the&nbsp;conclusion is as following:&nbsp;the&nbsp;workplace&nbsp;friendship&nbsp;has a positive&nbsp;influence&nbsp;on&nbsp;organizational&nbsp;citizenship&nbsp;behavior,&nbsp;the&nbsp;relational energy works as an agent between&nbsp;workplace&nbsp;friendship&nbsp;and&nbsp;organizational&nbsp;citizenship&nbsp;behavior, and&nbsp;workplace&nbsp;social&nbsp;self-efficacy up-regulates&nbsp;the&nbsp;direct&nbsp;effect&nbsp;of&nbsp;workplace&nbsp;friendship&nbsp;on&nbsp;organizational&nbsp;citizenship&nbsp;behavior.</p

Design of Emergency Evacuation Scheme for Louvre

Abstract In this paper, we used four steps in analyzing the optimal model of evacuation within the Louvre. For step 1, we refer to the traffic concept in the Dynamic Network Flow Model to define the export throughput. For step 2, considering that the original floor plan is segmented with pixel points as a unit with high complexity and little meaning, we simplify the floor plan when the model is guaranteed to be true. For step 3, we first mark the exit node, make its dual graph, and draw the point chain containing the exit node, which can divide the original image into several pieces according to the area. Breadth-First Search from each egress node can mark themselves with color, ownership and other information. For Step 4, in order to get the optimal segmentation which satisfies the definition of reasonable segmentation edge set, we use Genetic Algorithm to solve the optimization problem. A sequence consisting of the sequence numbers in the set of Edge-Cut is encoded as a gene in the Genetic Algorithm and iterated by the Theory of Chromosome Cross-Variation to obtain an optimal solution. Finally, we have designed a scientific and complete emergency evacuation plan.</jats:p

360VOT: A New Benchmark Dataset for Omnidirectional Visual Object Tracking

360° images can provide an omnidirectional field of view which is important for stable and long-term scene perception. In this paper, we explore 360° images for visual object tracking and perceive new challenges caused by large distortion, stitching artifacts, and other unique attributes of 360° images. To alleviate these problems, we take advantage of novel representations of target localization, i.e., bounding field-of-view, and then introduce a general 360 tracking framework that can adopt typical trackers for omnidirectional tracking. More importantly, we propose a new large-scale omnidirectional tracking benchmark dataset, 360VOT, in order to facilitate future research. 360VOT contains 120 sequences with up to 113K high-resolution frames in equirectangular projection. The tracking targets cover 32 categories in diverse scenarios. Moreover, we provide 4 types of unbiased ground truth, including (rotated) bounding boxes and (rotated) bounding field-of-views, as well as new metrics tailored for 360° images which allow for the accurate evaluation of omnidirectional tracking performance. Finally, we extensively evaluated 20 state-of-the-art visual trackers and provided a new baseline for future comparisons. Homepage: https://360vot.hkustvgd.com © 2023 IEEE