scholarly journals Modeling Pedestrian Motion in Crowded Scenes Based on the Shortest Path Principle

2021 ◽  
Vol 12 (1) ◽  
pp. 381
Author(s):  
Yi Zou ◽  
Yuncai Liu
Keyword(s):  
Shortest Path ◽  
State Of The Art ◽  
Meaningful Work ◽  
Movement Behavior ◽  
Motion Model ◽  
Human Dynamics ◽  
Motion Trajectories ◽  
Crowd Motion ◽  
Crowded Scenes ◽  
Part Motion

In the computer vision field, understanding human dynamics is not only a great challenge but also very meaningful work, which plays an indispensable role in public safety. Despite the complexity of human dynamics, physicists have found that pedestrian motion in a crowd is governed by some internal rules, which can be formulated as a motion model, and an effective model is of great importance for understanding and reconstructing human dynamics in various scenes. In this paper, we revisit the related research in social psychology and propose a two-part motion model based on the shortest path principle. One part of the model seeks the origin and destination of a pedestrian, and the other part generates the movement path of the pedestrian. With the proposed motion model, we simulated the movement behavior of pedestrians and classified them into various patterns. We next reconstructed the crowd motions in a real-world scene. In addition, to evaluate the effectiveness of the model in crowd motion simulations, we created a new indicator to quantitatively measure the correlation between two groups of crowd motion trajectories. The experimental results show that our motion model outperformed the state-of-the-art model in the above applications.

scholarly journals On the design of traps for feeding 3D parts on vibratory tracks

Robotica ◽  
2008 ◽  
Vol 26 (4) ◽  
pp. 537-550 ◽  
Author(s):  
Onno C. Goemans ◽  
A. Frank van der Stappen
Keyword(s):  
Geometric Structure ◽  
State Of The Art ◽  
Motion Model ◽  
Trap Design ◽  
Design Algorithm ◽  
New Class ◽  
Complete Set ◽  
Algorithmic Design ◽  
Bowl Feeder ◽  
Part Motion

SUMMARYIn the context of automated feeding (orienting) of industrial parts, we study the algorithmic design of traps in the bowl feeder track that filter out all but one orientation of a given polyhedral part. We propose a new class of traps that removes a V-shaped portion of the track. The proposed work advances the state-of-the-art in algorithmic trap design by extending earlier work1,6,17—which focuses solely on 2D parts—to 3D parts, and by incorporating a more realistic part motion model in the design algorithm. We exploit the geometric structure of the design problem and build on concepts and techniques from computational geometry to obtain an efficient algorithm that reports the complete set of valid traps.

An experimental evaluation and guideline for path finding in weighted dynamic network

2021 ◽  
Vol 14 (11) ◽  
pp. 2127-2140
Author(s):  
Mengxuan Zhang ◽  
Lei Li ◽  
Xiaofang Zhou
Keyword(s):  
Shortest Path ◽  
State Of The Art ◽  
Dynamic Networks ◽  
Real Life ◽  
Dynamic Network ◽  
Problem Space ◽  
Network Applications ◽  
Complete Problem ◽  
Path Computation ◽  
Shortest Path Computation

Shortest path computation is a building block of various network applications. Since real-life networks evolve as time passes, the Dynamic Shortest Path (DSP) problem has drawn lots of attention in recent years. However, as DSP has many factors related to network topology, update patterns, and query characteristics, existing works only test their algorithms on limited situations without sufficient comparisons with other approaches. Thus, it is still hard to choose the most suitable method in practice. To this end, we first identify the determinant dimensions and constraint dimensions of the DSP problem and create a complete problem space to cover all possible situations. Then we evaluate the state-of-the-art DSP methods under the same implementation standard and test them systematically under a set of synthetic dynamic networks. Furthermore, we propose the concept of dynamic degree to classify the dynamic environments and use throughput to evaluate their performance. These results can serve as a guideline to find the best solution for each situation during system implementation and also identify research opportunities. Finally, we validate our findings on real-life dynamic networks.

scholarly journals Accelerating eye movement research via accurate and affordable smartphone eye tracking

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Nachiappan Valliappan ◽  
Na Dai ◽  
Ethan Steinberg ◽  
Junfeng He ◽  
Kantwon Rogers ◽  
...  
Keyword(s):  
Machine Learning ◽  
Eye Tracking ◽  
Eye Movement ◽  
Vision Research ◽  
State Of The Art ◽  
Movement Behavior ◽  
Natural Image ◽  
Explicit Consent ◽  
Using Data ◽  
Additional Hardware

Abstract Eye tracking has been widely used for decades in vision research, language and usability. However, most prior research has focused on large desktop displays using specialized eye trackers that are expensive and cannot scale. Little is known about eye movement behavior on phones, despite their pervasiveness and large amount of time spent. We leverage machine learning to demonstrate accurate smartphone-based eye tracking without any additional hardware. We show that the accuracy of our method is comparable to state-of-the-art mobile eye trackers that are 100x more expensive. Using data from over 100 opted-in users, we replicate key findings from previous eye movement research on oculomotor tasks and saliency analyses during natural image viewing. In addition, we demonstrate the utility of smartphone-based gaze for detecting reading comprehension difficulty. Our results show the potential for scaling eye movement research by orders-of-magnitude to thousands of participants (with explicit consent), enabling advances in vision research, accessibility and healthcare.

scholarly journals Parallel Ant Colony Algorithm for Shortest Path Problem

2019 ◽  
Author(s):  
Géza Katona ◽  
Balázs Lénárt ◽  
János Juhász
Keyword(s):  
Parallel Computing ◽  
Shortest Path ◽  
Ant Colony Algorithm ◽  
State Of The Art ◽  
Shortest Path Problem ◽  
Ant Colony ◽  
Parameter Study ◽  
Real Network

During travelling, more and more information must be taken into account, and travelers have to make several complex decisions. In order to support these decisions, IT solutions are unavoidable, and as the computational demand is constantly growing, the examination of state-of-the-art methodologies is necessary. In our research, a parallelized Ant Colony algorithm was investigated, and a parameter study on a real network has been made. The aim was to inspect the sensibility of the method and to demonstrate its applicability in a multi-threaded system (e.g. Cloud-based systems). Based on the research, increased effectiveness can be reached by using more threads. The novelty of the paper is the usage of the processors’ parallel computing capability for routing with the Ant Colony algorithm.

State-of-the-art crowd motion simulation models

2013 ◽  
Vol 37 ◽  
pp. 193-209 ◽  
Author(s):  
Dorine C. Duives ◽  
Winnie Daamen ◽  
Serge P. Hoogendoorn
Keyword(s):  
State Of The Art ◽  
Simulation Models ◽  
Motion Simulation ◽  
Crowd Motion

scholarly journals Reliable service chain orchestration for scalable data-intensive computing at infrastructure edges

2019 ◽  
Author(s):  
◽  
Dmitrii Yurievich Chemodanov
Keyword(s):  
Computer Vision ◽  
Data Collection ◽  
Shortest Path ◽  
State Of The Art ◽  
Cloud Infrastructure ◽  
Data Intensive Computing ◽  
Video Analytics ◽  
Service Chain ◽  
Data Intensive ◽  
Reliable Service

In the event of natural or man-made disasters, geospatial video analytics is valuable to provide situational awareness that can be extremely helpful for first responders. However, geospatial video analytics demands massive imagery/video data 'collection' from Internet-of-Things (IoT) and their seamless 'computation/consumption' within a geo-distributed (edge/core) cloud infrastructure in order to cater to user Quality of Experience (QoE) expectations. Thus, the edge computing needs to be designed with a reliable performance while interfacing with the core cloud to run computer vision algorithms. This is because infrastructure edges near locations generating imagery/video content are rarely equipped with high-performance computation capabilities. This thesis addresses challenges of interfacing edge and core cloud computing within the geo-distributed infrastructure as a novel 'function-centric computing' paradigm that brings new insights to computer vision, edge routing and network virtualization areas. Specifically, we detail the state-of-the-art techniques and illustrate our new/improved solution approaches based on function-centric computing for the two problems of: (i) high-throughput data collection from IoT devices at the wireless edge, and (ii) seamless data computation/consumption within the geo-distributed (edge/core) cloud infrastructure. To address (i), we present a novel deep learning-augmented geographic edge routing that relies on physical area knowledge obtained from satellite imagery. To address (ii), we describe a novel reliable service chain orchestration framework that builds upon microservices and utilizes a novel 'metapath composite variable' approach supported by a constrained-shortest path finder. Finally, we show both analytically and empirically, how our geographic routing, constrained shortest path finder and reliable service chain orchestration approaches that compose our function-centric computing framework are superior than many traditional and state-of-the-art techniques. As a result, we can significantly speedup (up to 4 times) data-intensive computing at infrastructure edges fostering effective disaster relief coordination to save lives.

scholarly journals HESML: a real-time semantic measures library for the biomedical domain with a reproducible survey

2022 ◽  
Vol 23 (1) ◽  
Author(s):  
Juan J. Lastra-Díaz ◽  
Alicia Lara-Clares ◽  
Ana Garcia-Serrano
Keyword(s):  
Real Time ◽  
Semantic Similarity ◽  
Similarity Measure ◽  
Shortest Path ◽  
State Of The Art ◽  
Biomedical Domain ◽  
Snomed Ct ◽  
Shortest Path Algorithm ◽  
Semantic Similarity Measure ◽  
Current State

Abstract Background Ontology-based semantic similarity measures based on SNOMED-CT, MeSH, and Gene Ontology are being extensively used in many applications in biomedical text mining and genomics respectively, which has encouraged the development of semantic measures libraries based on the aforementioned ontologies. However, current state-of-the-art semantic measures libraries have some performance and scalability drawbacks derived from their ontology representations based on relational databases, or naive in-memory graph representations. Likewise, a recent reproducible survey on word similarity shows that one hybrid IC-based measure which integrates a shortest-path computation sets the state of the art in the family of ontology-based semantic measures. However, the lack of an efficient shortest-path algorithm for their real-time computation prevents both their practical use in any application and the use of any other path-based semantic similarity measure. Results To bridge the two aforementioned gaps, this work introduces for the first time an updated version of the HESML Java software library especially designed for the biomedical domain, which implements the most efficient and scalable ontology representation reported in the literature, together with a new method for the approximation of the Dijkstra’s algorithm for taxonomies, called Ancestors-based Shortest-Path Length (AncSPL), which allows the real-time computation of any path-based semantic similarity measure. Conclusions We introduce a set of reproducible benchmarks showing that HESML outperforms by several orders of magnitude the current state-of-the-art libraries in the three aforementioned biomedical ontologies, as well as the real-time performance and approximation quality of the new AncSPL shortest-path algorithm. Likewise, we show that AncSPL linearly scales regarding the dimension of the common ancestor subgraph regardless of the ontology size. Path-based measures based on the new AncSPL algorithm are up to six orders of magnitude faster than their exact implementation in large ontologies like SNOMED-CT and GO. Finally, we provide a detailed reproducibility protocol and dataset as supplementary material to allow the exact replication of all our experiments and results.

A mathematical framework for a crowd motion model

2008 ◽  
Vol 346 (23-24) ◽  
pp. 1245-1250 ◽  
Author(s):  
Bertrand Maury ◽  
Juliette Venel
Keyword(s):  
Mathematical Framework ◽  
Motion Model ◽  
Crowd Motion
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