Browsing by Author "Jaison, Alex"

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    Report on Vehicle Detection System
    (2017-08-03T07:22:36Z) Jaison, Alex; Anu, Thomas; Rahul, Ramesh
    Aerial surveillance is widely used in military and civilian uses for monitoring resources such as forests crops and observing enemy activities. Aerial surveillance cover large spatial area and hence it is suitable for monitoring fast moving targets. Vehicle detection in aerial images has important military and civilian uses. It has many applications in the field of traffic monitoring and management. Detecting vehicle is an important task in areal video analysis. The challenges of vehicle detection in aerial surveillance include camera motions such as panning, tilting, and rotation. In addition, airborne platforms at different heights result in different sizes of target objects. The view of vehicles will vary according to the camera positions, lightning conditions. A vehicle detection system for aerial surveillance using pixel wise classification method is implemented. Relations among neighboring pixels in a region are preserved in the feature extraction process. Local features such as edges and corners are considered. For edge detection, we apply thresholds, which increases the adaptability and the accuracy for detection in various aerial images. Afterward, a Support Vector Machine(SVM) is constructed for the classification purpose. Thus convert regional local features into quantitative observations that can be referenced. when applying pixel wise classification via SVM. Experiments were conducted on a wide variety of aerial videos. The results can be applied on aerial surveillance images taken at different heights and under different camera angles.
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    Vehicle Detection System
    (2017-07-18T10:11:10Z) Jaison, Alex; Anu, Thomas; Rahul, Ramesh
    Aerial surveillance is widely used in military and civilian uses for monitoring resources such as forests crops and observing enemy activities. Aerial surveillance cover large spatial area and hence it is suitable for monitoring fast moving targets. Vehicle detection in aerial images has important military and civilian uses. It has many applications in the field of traffic monitoring and management. Detecting vehicle is an important task in areal video analysis. The challenges of vehicle detection in aerial surveillance include camera motions such as panning, tilting, and rotation. In addition, airborne platforms at different heights result in different sizes of target objects. The view of vehicles will vary according to the camera positions, lightning conditions. A vehicle detection system for aerial surveillance using pixel wise classification method is implemented. Relations among neighboring pixels in a region are preserved in the feature extraction process. Local features such as edges and corners are considered. For edge detection, we apply thresholds, which increases the adaptability and the accuracy for detection in various aerial images. Afterward, a Support Vector Machine(SVM) is constructed for the classification purpose. Thus convert regional local features into quantitative observations that can be referenced. when applying pixel wise classification via SVM. Experiments were conducted on a wide variety of aerial videos. The results can be applied on aerial surveillance images taken at different heights and under different camera angles.