A Comprehensive Review Towards Appropriate Feature Selection for Moving Object Detection Using Aerial Images

Efficient feature extraction for moving object using aerial images is still an unsolved issue in computer vision, image processing and pattern recognition research domains. Aerial types of images contain various environmental constraints due to capture frames from various altitudes level, i.e. illumination, shadows, occlusion. For this reason, appropriate feature selection for those types of images needs more attention by the researchers to improve detection rate with fast and computationally less complex features extraction method. This research performed comprehensive review with critical analysis for using various features with various methods for moving object detection using aerial images. In this context, three aspects for critical analysis of using various features are identified followed by challenges of using various features. After that, existing methods with advantages and barriers are comprehensively described with various constraints claimed by the previous research. Next, justification for the need of new feature selection is elaborated for optimum detection performance. Later, adequate validation matrics are illustrated to evaluate various features based moving object detection using aerial images performed in the previous research. The overall review performed in this paper have been comprehensively studied and expected to contribute significantly in computer vision, image processing pattern recognition research field.

[1]  Anton Satria Prabuwono,et al.  Moment Feature Based Fast Feature Extraction Algorithm for Moving Object Detection Using Aerial Images , 2015, PloS one.

[2]  Matthew E. Antone,et al.  Detecting and tracking all moving objects in wide-area aerial video , 2012, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

[3]  Anton Satria Prabuwono,et al.  Real Time Vision Based Object Detection from UAV Aerial Images: A Conceptual Framework , 2013, FIRA.

[4]  Yu Wang,et al.  Detection and Classification of Moving Vehicle From Video Using Multiple Spatio-Temporal Features , 2019, IEEE Access.

[5]  Farid Melgani,et al.  A SIFT-SVM method for detecting cars in UAV images , 2012, 2012 IEEE International Geoscience and Remote Sensing Symposium.

[6]  Fuqiang Liu,et al.  Stationary vehicle detection in aerial surveillance with a UAV , 2012, 2012 8th International Conference on Information Science and Digital Content Technology (ICIDT2012).

[7]  Mubarak Shah,et al.  Human identity recognition in aerial images , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[8]  Yi-Ta Wu,et al.  A Hybrid Moving Object Detection Method for Aerial Images , 2010, PCM.

[9]  Anton Satria Prabuwono,et al.  Motion analysis for moving object detection from UAV aerial images: A review , 2014, 2014 International Conference on Informatics, Electronics & Vision (ICIEV).

[10]  Terrence Fong,et al.  Vehicle detection from aerial imagery , 2011, 2011 IEEE International Conference on Robotics and Automation.

[11]  S. Vasavi,et al.  Moving Object Classification Under Illumination Changes Using Binary Descriptors , 2019, Optoelectronics in Machine Vision-Based Theories and Applications.

[12]  Mahmoud A. Mofaddel,et al.  Fast and accurate approaches for image and moving object segmentation , 2011, The 2011 International Conference on Computer Engineering & Systems.

[13]  Anton Satria Prabuwono,et al.  Moving Object Detection Using Dynamic Motion Modelling from UAV Aerial Images , 2014, TheScientificWorldJournal.

[14]  Teddy Mantoro,et al.  Vision-Based Human Face Recognition Using Extended Principal Component Analysis , 2013, Int. J. Mob. Comput. Multim. Commun..

[15]  Michael Teutsch,et al.  Spatio-temporal fusion of object segmentation approaches for moving distant targets , 2012, 2012 15th International Conference on Information Fusion.

[16]  H. Abdul Rauf,et al.  Edgelet based human detection and tracking by combined segmentation and soft decision , 2009, 2009 International Conference on Control, Automation, Communication and Energy Conservation.

[17]  Stefano Pantaleoni,et al.  Bone Mineral Density at Diagnosis of Celiac Disease and after 1 Year of Gluten-Free Diet , 2014, TheScientificWorldJournal.

[18]  Xiaofeng Liu,et al.  Vehicle detection methods from an unmanned aerial vehicle platform , 2012, 2012 IEEE International Conference on Vehicular Electronics and Safety (ICVES 2012).

[19]  Qian Yu,et al.  Motion pattern interpretation and detection for tracking moving vehicles in airborne video , 2009, CVPR.

[20]  Toby P. Breckon,et al.  Real-time people and vehicle detection from UAV imagery , 2011, Electronic Imaging.

[21]  U. U. Sheikh,et al.  Moving object detection using image registration for a moving camera platform , 2012, 2012 IEEE International Conference on Control System, Computing and Engineering.

[22]  Hongguang Li,et al.  Aerial video image object detection and tracing based on motion vector compensation and statistic analysis , 2009, 2009 Asia Pacific Conference on Postgraduate Research in Microelectronics & Electronics (PrimeAsia).

[23]  Sheng Wang.  Vehicle Detection on Aerial Images by Extracting Corner Features for Rotational Invariant Shape Matching , 2011, 2011 IEEE 11th International Conference on Computer and Information Technology.

[24]  Larry S. Davis,et al.  Vehicle Detection Using Partial Least Squares , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[25]  Abdenbi Mazoul,et al.  A Fast Road Obstacle Detection Using Association and Symmetry recognition , 2019, 2019 International Conference on Wireless Technologies, Embedded and Intelligent Systems (WITS).

[26]  Hsu-Yung Cheng,et al.  Vehicle Detection in Aerial Surveillance Using Dynamic Bayesian Networks , 2012, IEEE Transactions on Image Processing.

[27]  Xiaoting Wang,et al.  Vehicle detection based on morphology from highway aerial images , 2012, 2012 IEEE International Geoscience and Remote Sensing Symposium.

[28]  Long Chen,et al.  A coarse-to-fine approach for vehicles detection from aerial images , 2012, 2012 International Conference on Computer Vision in Remote Sensing.

[29]  Lu Wang,et al.  The adaptive compensation algorithm for small UAV image stabilization , 2012, 2012 IEEE International Geoscience and Remote Sensing Symposium.

[30]  Witold Czajewski,et al.  Moving Objects Detection and Tracking Framework for UAV-based Surveillance , 2010, 2010 Fourth Pacific-Rim Symposium on Image and Video Technology.