Moving Object Detection and Tracking in Wide Area Motion Imagery

2014 ◽  
pp. 49-70 ◽  
Author(s):  
Varun Santhaseelan ◽  
Vijayan K. Asari
Keyword(s):  
Object Detection ◽  
Moving Object Detection ◽  
Moving Object ◽  
Wide Area ◽  
Object Detection And Tracking ◽  
Detection And Tracking ◽  
Motion Imagery

scholarly journals Spatial pyramid context-aware moving object detection and tracking for full motion video and wide aerial motion imagery

2017 ◽  
Author(s):  
◽  
Mahdieh Poostchi
Keyword(s):  
Object Detection ◽  
Tracking System ◽  
Moving Object Detection ◽  
Moving Object ◽  
Object Detection And Tracking ◽  
Detection And Tracking ◽  
Motion Imagery ◽  
Integral Histogram ◽  
Motion Video ◽  
Spatial Pyramid

A robust and fast automatic moving object detection and tracking system is essential to characterize target object and extract spatial and temporal information for different functionalities including video surveillance systems, urban traffic monitoring and navigation, robotic, medical imaging, etc. A reliable detecting and tracking system is required to generalize across huge variations in object appearance changes due to camera viewpoint, pose, scale, lighting conditions, imaging quality or occlusions and achieve real-time performance. In this dissertation, I present a collaborative Spatial Pyramid Context-aware moving object detection and Tracking system (SPCT). The proposed visual tracker is composed of one master tracker that usually relies on visual object features and two auxiliary trackers based on object temporal motion information that will be called dynamically to assist master tracker. SPCT utilizes image spatial context at different level to make the video tracking system resistant to occlusion, background noise and improve target localization accuracy and robustness. We chose a pre-selected seven-channel complementary features including RGB color, intensity and spatial pyramid of HoG to encode object color, shape and spatial layout information. We exploit integral histogram as building block to meet the demands of real-time performance. A novel fast algorithm is presented to accurately evaluate spatially weighted local histograms in constant time complexity using an extension of the integral histogram method. Different techniques are explored to efficiently compute integral histogram on GPU architecture and applied for fast spatio-temporal median computations and 3D face reconstruction texturing. We proposed a multi-component framework based on semantic fusion of motion information with projected building footprint map to significantly reduce the false alarm rate in urban scenes with many tall structures. The experiments on extensive VOTC2016 benchmark dataset and aerial video confirm that combining complementary tracking cues in an intelligent fusion framework enables persistent tracking for Full Motion Video (FMV) and Wide Aerial Motion Imagery (WAMI).

Moving Object Detection and Tracking Based on the Contour Extraction and Centroid Representation

2019 ◽  
pp. 147-157
Author(s):  
Naveenkumar M ◽  
Sriharsha K. V. ◽  
Vadivel A
Keyword(s):  
Object Detection ◽  
Motion Tracking ◽  
Moving Object Detection ◽  
Moving Object ◽  
Absolute Difference ◽  
Contour Extraction ◽  
Object Detection And Tracking ◽  
Detection And Tracking ◽  
Novel Approach ◽  
Extraction Algorithm

This chapter presents a novel approach for moving object detection and tracking based on contour extraction and centroid representation (CECR). Firstly, two consecutive frames are read from the video, and they are converted into grayscale. Next, the absolute difference is calculated between them and the result frame is converted into binary by applying gray threshold technique. The binary frame is segmented using contour extraction algorithm. The centroid representation is used for motion tracking. In the second stage of experiment, initially object is detected by using CECR and motion of each track is estimated by Kalman filter. Experimental results show that the proposed method can robustly detect and track the moving object.

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