ISSN: 2490-3477

E-ISSN: 2490-3485

TTTP

Traffic and Transport Theory and Practice

Journal for Traffic and Transport Research and Application

Vol. 9 No. 2 (2024): TTTP - APEIRON

Pavel Slivnitsin, Leonid Mylnikov, Egor Efimov

Component-Based Object Recognition Algorithm

Original scientific paper

DOI: 10.7251/JTTTP2402069S

Abstract

The paper presents an approach to object recognition based on the hypothesis of representing objects using a set of geometric primitives and relations between them. The goal of the paper is to develop a method for object recognition in the environment, which allows to recognize objects based on their description. For this purpose, the following tasks are solved: the recognition of a set of geometrical objects (primitives), the estimation of relations between primitives and the search of correspondences between the found primitives and relations and the defined templates (descriptions objects). The set of geometric primitives is selected taking into account the nature of the subject area of the objects to be recognized. The paper presents object recognition examples through the use of the method proposed. As a result, the operability of the proposed object recognition method is confirmed. An object description method has been developed. For experiments, the images of primitives were used generated in the Blender 3D, as well as photos of primitives from the kid’s toy constructor. The primitive detection model was trained on a training sample consisting of 1000 artificial images and 50 real images. The research results can be applied in algorithms for recognizing traffic participants as well as traffic signaling objects

Keywords: object recognition, object detection, recognition by components, computer vision, relation encoding, recognition algorithm.

Vol. 9 No. 1 (2024): TTTP - APEIRON

Vladimir Gatarić, Tanja Marjanac, Vuk Bogdanović

The influence of the corona virus pandemic on the characteristics of vehicle flow on the e-661 highway

Original scientific paper

DOI: 10.7251/JTTTP2401016G

Abstract

In this work, the characteristics of the traffic flow on the section of the Gradiška- Banja Luka highway, which is part of the European road route E-661, were analyzed in the period from 2019 to 2022. Data on the size of flow requests were taken from the database of the toll station “Jakupovci” on the Gradiška- Banja Luka highway. When defining the size of the flow request, the structure of the traffic flow was also taken into account, in accordance with the categories according to which the toll is collected. The period in which the analysis of flow characteristics was performed also includes the period in which the coronavirus pandemic reigned, when certain travel rules and prohibitions were in force. In accordance with that, the work will specifically analyze the impact of the COVID 19 pandemic on the characteristics of the traffic flow on the Gradiška- Banja Luka highway section. Given that the

„Jakupovci“ toll station is the busiest toll station on the Gradiška- Banja Luka highway, the results of the analysis can be applied to other sections of highways in the Republic of Srpska.

Keywords: Traffic flow characteristics, vehicle flow, COVID 19 pandemic, Gradiška- Banja Luka highway

Vol. 9 No. 2 (2024): TTTP - APEIRON

Pavel Slivnitsin, Leonid Mylnikov, Egor Efimov

Component-Based Object Recognition Algorithm

Original scientific paper

DOI: 10.7251/JTTTP2402069S

Abstract

The paper presents an approach to object recognition based on the hypothesis of representing objects using a set of geometric primitives and relations between them. The goal of the paper is to develop a method for object recognition in the environment, which allows to recognize objects based on their description. For this purpose, the following tasks are solved: the recognition of a set of geometrical objects (primitives), the estimation of relations between primitives and the search of correspondences between the found primitives and relations and the defined templates (descriptions objects). The set of geometric primitives is selected taking into account the nature of the subject area of the objects to be recognized. The paper presents object recognition examples through the use of the method proposed. As a result, the operability of the proposed object recognition method is confirmed. An object description method has been developed. For experiments, the images of primitives were used generated in the Blender 3D, as well as photos of primitives from the kid’s toy constructor. The primitive detection model was trained on a training sample consisting of 1000 artificial images and 50 real images. The research results can be applied in algorithms for recognizing traffic participants as well as traffic signaling objects

Keywords : object recognition, object detection, recognition by components, computer vision, relation encoding, recognition algorithm.