Multi-Pedestrian Tracking with Clusters

Optimized Implementation of Pedestrian Tracking Using Multiple Cues on GPU

IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences ◽

10.1587/transfun.e94.a.2323 ◽

2011 ◽

Vol E94-A (11) ◽

pp. 2323-2333

Author(s):

Ryusuke MIYAMOTO ◽

Hiroki SUGANO

Keyword(s):

Pedestrian Tracking ◽

Multiple Cues

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Smartphone-Based Inertial Odometry for Blind Walkers

Sensors ◽

10.3390/s21124033 ◽

2021 ◽

Vol 21 (12) ◽

pp. 4033

Author(s):

Peng Ren ◽

Fatemeh Elyasi ◽

Roberto Manduchi

Keyword(s):

Particle Filtering ◽

Inertial Sensors ◽

State Of The Art ◽

Inertial Sensor ◽

Mean Shift ◽

Gait Pattern ◽

Comparative Assessment ◽

Pedestrian Tracking ◽

Step Counter ◽

Assisted Navigation

Pedestrian tracking systems implemented in regular smartphones may provide a convenient mechanism for wayfinding and backtracking for people who are blind. However, virtually all existing studies only considered sighted participants, whose gait pattern may be different from that of blind walkers using a long cane or a dog guide. In this contribution, we present a comparative assessment of several algorithms using inertial sensors for pedestrian tracking, as applied to data from WeAllWalk, the only published inertial sensor dataset collected indoors from blind walkers. We consider two situations of interest. In the first situation, a map of the building is not available, in which case we assume that users walk in a network of corridors intersecting at 45° or 90°. We propose a new two-stage turn detector that, combined with an LSTM-based step counter, can robustly reconstruct the path traversed. We compare this with RoNIN, a state-of-the-art algorithm based on deep learning. In the second situation, a map is available, which provides a strong prior on the possible trajectories. For these situations, we experiment with particle filtering, with an additional clustering stage based on mean shift. Our results highlight the importance of training and testing inertial odometry systems for assisted navigation with data from blind walkers.

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