CSE 321 – Object Detection & Tracking

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Presentation transcript:

CSE 321 – Object Detection & Tracking Todd Heath

Classes, Responsibility, Collaboration (CRC) Card Class: BallTracker Responsibilities: Collaborators: Initialization * Bluetooth Find Ball * Camera Seek Object * Hard Drive Navigate to Target * IR Sensors Play Song * Motor Speaker * Todd Heath

Project Information Identify and seek out targets of a specific color. While seeking valid targets, obstacles should be avoided. Navigate more precisely as distance to target decreases. Keep track of target size as navigating to target. Target should get larger as approaching. Export animated GIFs of Scribbler point of view at program termination (Color, Blob) Play song at beginning and end of program.

Lessons Learned How to make a Python module. Scribbler uses YUV color space instead of RGB. Blob detection very light sensitive. Edge detection can be useful for determining object boundaries and walls versus floors. Pattern matching would have been useful for identifying valid targets versus background noise. Race conditions with Scribbler sometime occur on rough surfaces.

Video Demonstration

Scribbler Point of View Color Image Blob Image