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Intro to Object Detection with SSD

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Thomas Delteil

This document introduces single-shot multibox object detection, which uses a single deep neural network to predict bounding boxes and class probabilities for objects in an image. It discusses object detection algorithms in general and compares approaches. For single-shot detection, default bounding boxes of different scales and ratios are generated to match objects. The network architecture outputs class probabilities and box offsets for the default boxes.

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© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark MXNet Team An Introduction to Single-Shot MultiBox Object-Detection
© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark https://medium.com/comet-app/review-of-deep-learning-algorithms-for-object- detection-c1f3d437b852
© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark What is Object Detection
© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Comparison of Algorithms https://medium.com/@jonathan_hui/object-detection-speed-and-accuracy- comparison-faster-r-cnn-r-fcn-ssd-and-yolo-5425656ae359
© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark What does the input look like?
© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark What does the training data look like? [xmin, ymin, xmax, ymax, class_id] [[0.3, 0.1088, 1, 1, 1], [0.0, 0.3638, 0.8, 1, 2]]
© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Intersection over Union https://www.pyimagesearch.com/2016/11/07/intersection-over-union-iou-for- object-detection/
© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Single-Shot Detection Default Boxes Different number of targets per training sample… => Use fixed number of generated targets!
© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Single-Shot Detection Architecture
© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Single-Shot Detection Architecture
© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Default boxes the Receptive field
© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Another example https://medium.com/@jonathan_hui/ssd-object-detection-single-shot-multibox- detector-for-real-time-processing-9bd8deac0e06
© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark https://medium.com/@jonathan_hui/ssd-object-detection-single-shot-multibox- detector-for-real-time-processing-9bd8deac0e06
© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark https://medium.com/@jonathan_hui/ssd-object-detection-single-shot-multibox- detector-for-real-time-processing-9bd8deac0e06

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Intro to Object Detection with SSD

  • 1. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark MXNet Team An Introduction to Single-Shot MultiBox Object-Detection
  • 2. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark https://medium.com/comet-app/review-of-deep-learning-algorithms-for-object- detection-c1f3d437b852
  • 3. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark What is Object Detection
  • 4. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Comparison of Algorithms https://medium.com/@jonathan_hui/object-detection-speed-and-accuracy- comparison-faster-r-cnn-r-fcn-ssd-and-yolo-5425656ae359
  • 5. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark What does the input look like?
  • 6. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark What does the training data look like? [xmin, ymin, xmax, ymax, class_id] [[0.3, 0.1088, 1, 1, 1], [0.0, 0.3638, 0.8, 1, 2]]
  • 7. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Intersection over Union https://www.pyimagesearch.com/2016/11/07/intersection-over-union-iou-for- object-detection/
  • 8. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Single-Shot Detection Default Boxes Different number of targets per training sample… => Use fixed number of generated targets!
  • 9. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Single-Shot Detection Architecture
  • 10. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Single-Shot Detection Architecture
  • 11. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Default boxes the Receptive field
  • 12. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Another example https://medium.com/@jonathan_hui/ssd-object-detection-single-shot-multibox- detector-for-real-time-processing-9bd8deac0e06
  • 13. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark https://medium.com/@jonathan_hui/ssd-object-detection-single-shot-multibox- detector-for-real-time-processing-9bd8deac0e06
  • 14. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark https://medium.com/@jonathan_hui/ssd-object-detection-single-shot-multibox- detector-for-real-time-processing-9bd8deac0e06

Editor's Notes

  1. Mathew Hyperopt TPE (Tree Parzen Estimator)
  2. Natural Language Processing Sentiment analysis/mood
  3. ML was created to identify images of cats.
  4. Earlier layers detect primitives Later layers for bounding boxes