WEEK 8: WEB-ASSISTED OBJECT DETECTION ALEJANDRO TORROELLA & AMIR R. ZAMIR.

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Presentation transcript:

WEEK 8: WEB-ASSISTED OBJECT DETECTION ALEJANDRO TORROELLA & AMIR R. ZAMIR

GEOMETRY METHOD PROCEDURE For each query image we manually set orientation, angle of view, range of view, and location of camera. : Camera location : Object locations : Field of vision

GEOMETRY METHOD PROCEDURE Using the obtained FOV, select only the objects that are within the FOV Calculate the degrees from the left limit of the FOV and store in a vector specific to the object’s class

GEOMETRY METHOD PROCEDURE We then run our DPM detectors for the classes in question on the query image. Below are results for Street Lights (green) and Traffic Signals (red).

GEOMETRY METHOD PROCEDURE We sift through the detections that completely disagree with the “true” GIS layout.

GEOMETRY METHOD PROCEDURE We then sift through the detections again by size of bounding boxes (too large or too small)

GEOMETRY METHOD PROCEDURE

Once we’ve traversed through all the possible combinations, we display the detections that resulted in the minimum of the cost function.

GEOMETRY METHOD RESULTS: BEFORE

GEOMETRY METHOD RESULTS: AFTER GIS SIFT

GEOMETRY METHOD RESULTS: AFTER SIZE SIFT

GEOMETRY METHOD RESULTS: AFTER FUSION (ABS)

GEOMETRY METHOD RESULTS: AFTER FUSION (STD)

GEOMETRY METHOD RESULTS: BEFORE

GEOMETRY METHOD RESULTS: AFTER GIS SIFT

GEOMETRY METHOD RESULTS: AFTER SIZE SIFT

GEOMETRY METHOD RESULTS: AFTER FUSION (ABS)

GEOMETRY METHOD RESULTS: AFTER FUSION (STD)

GEOMETRY METHOD RESULTS: BEFORE

GEOMETRY METHOD RESULTS: AFTER GIS SIFT

GEOMETRY METHOD RESULTS: AFTER SIZE SIFT

GEOMETRY METHOD RESULTS: AFTER FUSION (ABS)

GEOMETRY METHOD RESULTS: AFTER FUSION (STD)

GEOMETRY METHOD RESULTS: BEFORE

GEOMETRY METHOD RESULTS: AFTER GIS SIFT

GEOMETRY METHOD RESULTS: AFTER SIZE SIFT

GEOMETRY METHOD RESULTS: AFTER FUSION (ABS)

GEOMETRY METHOD RESULTS: AFTER FUSION (STD)

GEOMETRY METHOD RESULTS: BEFORE

GEOMETRY METHOD RESULTS: AFTER GIS SIFT

GEOMETRY METHOD RESULTS: AFTER SIZE SIFT

GEOMETRY METHOD RESULTS: AFTER FUSION (ABS)

GEOMETRY METHOD RESULTS: AFTER FUSION (STD)

GEOMETRY METHOD RESULTS: BEFORE

GEOMETRY METHOD RESULTS: AFTER GIS SIFT

GEOMETRY METHOD RESULTS: AFTER SIZE SIFT

GEOMETRY METHOD RESULTS: AFTER FUSION (ABS)

GEOMETRY METHOD RESULTS: AFTER FUSION (STD)

GEOMETRY METHOD RESULTS: BEFORE

GEOMETRY METHOD RESULTS: AFTER GIS SIFT

GEOMETRY METHOD RESULTS: AFTER SIZE SIFT

GEOMETRY METHOD RESULTS: AFTER FUSION (ABS)

GEOMETRY METHOD RESULTS: AFTER FUSION (STD)

GEOMETRY METHOD RESULTS: BEFORE

GEOMETRY METHOD RESULTS: AFTER GIS SIFT

GEOMETRY METHOD RESULTS: AFTER SIZE SIFT

GEOMETRY METHOD RESULTS: AFTER FUSION (ABS)

GEOMETRY METHOD RESULTS: AFTER FUSION (STD)

GEOMETRY METHOD CONCLUSIONS Using the Standard deviation cost function resulted in better results compared to the Absolute value function on average. A more advanced cost function would probably result in even better results Results look promising considering we haven’t implemented a robust sensor model for creating the “true” GIS layout

GOALS FOR NEXT WEEK Implement a robust sensor model Look into more advanced cost functions Instead of crudely sifting through the bounding boxes by size using a threshold based on the size of the image, use the distances of the objects from the camera to estimate how large the bounding box should be.

THANK YOU FIN.