Practical 3D Tracking Using Low-Cost Cameras
Authors: Roman Barták, Michal Koutný, David Obdrzálek
IJCAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | This paper shows the possibility to track a single object using low-cost cameras on an ordinary laptop in a small-scale and mostly static environment. This solution is useful for standalone tracking in mobile robotics and particularly in the debugging phases, where the user needs to judge the robot movement system independently on what the robot claims.We present a practical way of assembling all the pieces to create a system working in real world and usable out of the box. |
| Researcher Affiliation | Academia | Roman Barták, Michal Koutný, David Obdržálek Charles University in Prague, Czech Republic |
| Pseudocode | No | The paper describes the algorithms used (e.g., color-based tracker, Kalman filter), but it does not present them in pseudocode or a clearly labeled algorithm block. |
| Open Source Code | No | The paper mentions 'Dove-Eye system' and provides a URL 'http://koutny.org/dove-eye/', but it does not explicitly state that the source code for the methodology described in this paper is publicly available at this link or in a repository. |
| Open Datasets | No | The paper describes a system for tracking an object in a live environment rather than training on a specific dataset. There is no mention of publicly available or open datasets used for training or evaluation. |
| Dataset Splits | No | The paper describes a live tracking system and does not mention using pre-defined datasets with specific training, validation, or test splits. |
| Hardware Specification | No | The paper mentions 'low-cost cameras' and an 'ordinary (Linux) laptop' but does not provide specific hardware details such as CPU/GPU models, memory, or detailed specifications. |
| Software Dependencies | No | The paper mentions the use of 'Open CV computer vision library' but does not specify a version number for OpenCV or any other software dependencies. |
| Experiment Setup | No | The paper describes the general system setup, including calibration and tracking methods, but it does not provide specific experimental setup details such as hyperparameter values, learning rates, batch sizes, or detailed training configurations. |