A Multi-Feature Part-Based Object Detection System
From Google TechTalks · 54:58
Show by Google TechTalks
Google Tech TalksMay 25, 2007ABSTRACTI will start with an overview on object recognition systems which use local features and analyze their strengths and weaknesses. I will then present a general purpose part-based object detection system which we evaluated on a benchmark pedestrian detection data set . In a first step, the system computes feature maps from the training images. It then randomly extracts a large number of rectangular parts from the feature maps and clusters the parts based on their feature similarity and their x-y-location in the feature maps. The cluster centers build an initial set of part templates from which the system selects a subset using the gentle-boost algorithm. The...Uploaded 08-10-07
More episodes of Google TechTalks
More episodes
- Threat Models for Memorization: Privacy, Copyright, and Everything In-Between
- Technology Assisted Reading Acquisition: Children Acquiring Literacy Naturally
- sex on the internet, the realities of porn, sexual privacy,
- Privacy Auditing of Large Language Models
- The Limits and Possibilities of One Run Auditing
- PhotoTechEDU Day 29: Photographing VR Panoramas
- Privacy Ripple Effects from Adding or Removing Personal Information in Language Model Training
- Inside VMware Fusion
- Java Posse Episode 100 (Live Special)
- Cascading Adversarial Bias from Injection to Distillation in Language Models
PodSearch is a free, independent podcast search engine. Read about PodSearch, the privacy policy or contact us.