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Published on Oct 20, 2015
Description: Demonstration of our novel tracking method that directly performs model based tracking on the raw infrared signal of a Time-Of-Flight camera. A table tennis ball falls towards the ground accelerated by gravity. The orange sphere depicts the output of the tracker. The time-of-flight depth reconstruction is shown in white. Even when the depth reconstruction fails due to fast motion of the object, our method can track the moving object.
Publication: Model-Based Tracking at 300Hz using Raw Time-of-Flight Observations, ICCV 2015
Authors: Jan Stühmer, Sebastian Nowozin, Andrew Fitzgibbon, Richard Szeliski, Travis Perry, Sunil Acharya, Daniel Cremers and Jamie Shotton
Abstract: Consumer depth cameras have dramatically improved our ability to track rigid, articulated, and deformable 3D objects in real-time. However, depth cameras have a limited temporal resolution (frame-rate) that restricts the accuracy and robustness of tracking, especially for fast or unpredictable motion. In this paper, we show how to perform model-based object tracking which allows us to reconstruct the object’s depth at an order of magnitude higher frame-rate through simple modifications to an off-the-shelf depth camera. We focus on phase-based time-of-flight (ToF) sensing, which reconstructs each low frame-rate depth image from a set of short exposure ‘raw’ infrared captures. These raw captures are taken in quick succession near the beginning of each depth frame, and differ in the modulation of their active illumination. We make two contributions. First, we detail how to perform model-based tracking against these raw captures. Second, we show that by reprogramming the camera to space the raw captures uniformly in time, we obtain a 10x higher frame-rate, and thereby improve the ability to track fast-moving objects.