Nearest First Traversing Graph for Simultaneous Object Tracking and Recognition

2007 ◽  
Author(s):  
Junya Sakagaito ◽  
Toshikazu Wada
Keyword(s):  
Object Tracking ◽  
Tracking And Recognition

Combining Ultrasonic Signals And Multi-Colored Images To Perform Object Tracking And Recognition In Low-Cost Robotic Platforms

2016 ◽  
Author(s):  
Danilo H. F. Menezes ◽  
Thiago D. Mendonca ◽  
Wolney M. Neto ◽  
Hendrik T. Macedo ◽  
Leonardo N. Matos
Keyword(s):  
Object Tracking ◽  
Low Cost ◽  
Ultrasonic Signals ◽  
Robotic Platforms ◽  
Tracking And Recognition

Object Tracking and Recognition Based on Reliability Assessment of Learning in Mobile Environments

2016 ◽  
Vol 94 (2) ◽  
pp. 267-282 ◽  
Author(s):  
Youngseop Kim ◽  
Woori Han ◽  
Yong-Hwan Lee ◽  
Cheong Ghil Kim ◽  
Kuinam J. Kim
Keyword(s):  
Object Tracking ◽  
Reliability Assessment ◽  
Mobile Environments ◽  
Assessment Of Learning ◽  
Tracking And Recognition

scholarly journals Monocular Robust Depth Estimation Vision System for Robotic Tasks Interventions in Metallic Targets

Sensors ◽  
2019 ◽  
Vol 19 (14) ◽  
pp. 3220 ◽  
Author(s):  
Carlos Veiga Almagro ◽  
Mario Di Castro ◽  
Giacomo Lunghi ◽  
Raúl Marín Prades ◽  
Pedro José Sanz Valero ◽  
...  
Keyword(s):  
Object Tracking ◽  
Vision System ◽  
Nuclear Research ◽  
Depth Estimation ◽  
Work Load ◽  
Manual Control ◽  
Repetitive Tasks ◽  
Autonomous Mode ◽  
Robotic Tasks ◽  
Tracking And Recognition

Robotic interventions in hazardous scenarios need to pay special attention to safety, as in most cases it is necessary to have an expert operator in the loop. Moreover, the use of a multi-modal Human-Robot Interface allows the user to interact with the robot using manual control in critical steps, as well as semi-autonomous behaviours in more secure scenarios, by using, for example, object tracking and recognition techniques. This paper describes a novel vision system to track and estimate the depth of metallic targets for robotic interventions. The system has been designed for on-hand monocular cameras, focusing on solving lack of visibility and partial occlusions. This solution has been validated during real interventions at the Centre for Nuclear Research (CERN) accelerator facilities, achieving 95% success in autonomous mode and 100% in a supervised manner. The system increases the safety and efficiency of the robotic operations, reducing the cognitive fatigue of the operator during non-critical mission phases. The integration of such an assistance system is especially important when facing complex (or repetitive) tasks, in order to reduce the work load and accumulated stress of the operator, enhancing the performance and safety of the mission.

Active multispot projection for object tracking and recognition

2004 ◽  
Author(s):  
Wei Su ◽  
Laurence G. Hassebrook ◽  
Veera G. Yalla
Keyword(s):  
Object Tracking ◽  
Tracking And Recognition

OBJECT TRACKING AND RECOGNITION BY EDGE MOTOCOMPENSATION

2003 ◽  
Author(s):  
L. CAPODIFERRO ◽  
M. GRILLI ◽  
F. IACOLUCCI ◽  
A. LAURENTI ◽  
G. JACOVITTI
Keyword(s):  
Object Tracking ◽  
Tracking And Recognition

scholarly journals Object Detection and Identification in Surveillance Images using Image Processing

2019 ◽  
Vol 9 (1S3) ◽  
pp. 300-305
Keyword(s):  
Image Processing ◽  
Object Detection ◽  
Object Tracking ◽  
Range Size ◽  
Its Sequence ◽  
Surveillance Camera ◽  
Color Range ◽  
Detection And Identification ◽  
Illumination Changes ◽  
Tracking And Recognition

The goal of object detection and identification in surveillance images using image processing is to detect a particular part of the image from surveillance camera like an object’s position, movement, and its sequence. Object tracking and recognition deal with recognizing the image of video which can differ in color, range, size, illumination changes with time and some cluttered images. As this paper has been surveying and an algorithm has been proposed and implemented, the identified object has freed from the shadow, clutter, illumination changes were detected and eliminated appropriately.

A novel segmentation method for object tracking and recognition

2007 ◽  
Author(s):  
Carmen Witte ◽  
Klaus Jäger ◽  
Marcus Hebel ◽  
Walter Armbruster
Keyword(s):  
Object Tracking ◽  
Segmentation Method ◽  
Tracking And Recognition
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