GPU detektor objektů ve videu

object detection, WaldBoost, GPU, OpenCL, LBP, LRD, LRP, CSLBP

Real-time object detection is a core part of various complex algorithms in surveillance systems, traffic monitoring, autonomous vehicles and many other fields. Object detection is one of most computationally demanded part of these algorithms. Especially real-time processing of high resolution, high refresh rate or multiple image-based streams without rescaling or frame dropping are hard to achieve.

Software "GPU object detector in video stream" is suitable to achieve these goals thanks to parallel GPU implementation of detection algorithm which includes several optimization techniques that improves performance of object detection. Output is represented as a text file in CSV format that consists of frame numbers, positions and sizes of detected objects. Description of object classes is represented as a pretrained WaldBoost classifiers which contains LBP/LRD/LRD/CSLBP patterns.