Seiko Epson Corporation

Ariel Shlomo Kelman

Andrei Mark Rotenstein

Jennifer Jianing Sun

Asheer Kasar Bachoo

Christina Melissa Sutanto

Systems and method for predicting performance of pipelines for object detection, pose estimation, and object tracking are provided. In one embodiment, a plurality of regressors are stored where each regressor may be trained for a specific object detection (OD), pose estimation (PE), and/or tracking pipeline, so that each regressor outputs a score equal to or greater than that of another regressor in response to a first feature vector as input, the first feature vector corresponding to a first object that is more suitable for the specific pipeline than other pipelines. A second feature vector is stored corresponding to a second object. The regressors are run with the second feature vector as input to derive respective scores, and a recommendation of at least one pipeline is indicated based on the derived scores with respect to the second object. OD/PE/tracking may then be performed using the at least one indicated pipeline.

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Toronto, Canada

Ariel Shlomo Kelman