Clustering based Image Segmentation and Tracking
In machine learning and computer vision, image segmentation and tracking forms critical components in many applications. Fast and efficient algorithms are required for some applications such as robotics. Mean shift (MS) qualifies as one of the most popular mode-seeking algorithms used for clustering and image segmentation.However, its computational cost required to find the neighbors of each data point is quadratic to the number of data points. Consequently, the vanilla MS appears to be very slow for large-scale datasets. In this talk, we discuss a mode-seeking algorithm called GridShift, with significant speedup and principally based on MS. The runtime of GridShift is linear in the number of active grid cells and exponential in the number of features. Therefore, it is ideal for large-scale low-dimensional applications such as object tracking and image segmentation.
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- Hyderabad, Andhra Pradesh
- India
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- Co-sponsored by SCIS, University of Hyderabad
- Starts 15 July 2023 09:05 AM UTC
- Ends 25 July 2023 09:05 AM UTC
- No Admission Charge