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Understanding Visual Recognition: Key Concepts and Applications in Object Detection

This overview introduces the fundamentals of visual recognition as explored by Jitendra Malik at UC Berkeley. It focuses on the PASCAL Visual Object Challenge, emphasizing object location, image segmentation, and categorization at multiple levels. Key concepts include the classification of objects, agents, and their interactions. The taxonomy of actions and gestures, as well as the importance of visual processing areas in rapid object detection, are discussed. The presentation highlights how features from biological visual systems inspire computer vision techniques, such as Convolutional Neural Networks.

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Understanding Visual Recognition: Key Concepts and Applications in Object Detection

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Presentation Transcript

  1. Visual Recognition:The Big Picture Jitendra Malik University of California at Berkeley

  2. The more you look, the more you see!

  3. PASCAL Visual Object Challenge

  4. We want to locate the object Orig. Image Segmentation Orig. Image Segmentation

  5. And we want to detect and label parts.. The Visually Tagged Human Project

  6. Water back Grass Tiger Tiger Sand head eye legs tail mouth shadow Categorization at Multiple Levels outdoor wildlife

  7. Examples of Actions • Movement and posture change • run, walk, crawl, jump, hop, swim, skate, sit, stand, kneel, lie, dance (various), … • Object manipulation • pick, carry, hold, lift, throw, catch, push, pull, write, type, touch, hit, press, stroke, shake, stir, turn, eat, drink, cut, stab, kick, point, drive, bike, insert, extract, juggle, play musical instrument (various)… • Conversational gesture • point, … • Sign Language

  8. We need to identify • Objects • Agents • Relationships among objects with objects, objects with agents, agents with agents … • Events and Actions

  9. Taxonomy and Partonomy • Taxonomy: E.g. Cats are in the order Felidae which in turn is in the class Mammalia • Recognition can be at multiple levels of categorization, or be identification at the level of specific individuals , as in faces. • Partonomy: Objects have parts, they have subparts and so on. The human body contains the head, which in turn contains the eyes. • These notions apply equally well to scenes and to activities. • Psychologists have argued that there is a “basic-level” at which categorization is fastest (Eleanor Rosch et al). • In a partonomy each level contributes useful information for recognition.

  10. Visual Processing Areas

  11. Macaque Visual Areas

  12. Object Detection can be very fast • On a task of judging animal vs no animal, humans can make mostly correct saccades in 150 ms (Kirchner & Thorpe, 2006) • Comparable to synaptic delay in the retina, LGN, V1, V2, V4, IT pathway. • Doesn’t rule out feed back but shows feed forward only is very powerful • Detection and categorization are practically simultaneous (Grill-Spector & Kanwisher, 2005)

  13. Hubel and Wiesel (1962) discovered orientation sensitive neurons in V1

  14. These cells respond to edges and bars ..

  15. Orientation based features were inspired by V1 (SIFT, GIST, HOG, GB etc)

  16. Attneave’s Cat (1954)Line drawings convey most of the information

  17. Rolls et al (2000)

  18. Convolutional Neural Networks (LeCun et al)

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