Learning environmental features for pose estimation

نویسندگان

  • Robert Sim
  • Gregory Dudek
چکیده

We present a method for learning a set of environmental features which are useful for pose estimation. The landmark learning mechanism is designed to be applicable to a wide range of environments, and generalized for different sensing modilities. In the context of computer vision, each landmark is detected as a local extremum of a measure of distinctiveness and represented by an appearance-based encoding which is exploited for matching. The set of obtained landmarks can be parameterized and then evaluated in terms of their utility for the task at hand. The method is used to motivate a general approach to task-oriented sensor fusion. We present experimental evidence that demonstrates the utility of the method.

منابع مشابه

SEDAI et al.: LOCALIZED FUSION OF FEATURES FOR 3D HUMAN POSE ESTIMATION 1 Localized fusion of Shape and Appearance features for 3D Human Pose Estimation

This paper presents a learning-based method for combining the shape and appearance feature types for 3D human pose estimation from single-view images. Our method is based on clustering the 3D pose space into several modular regions and learning the regressors for both feature types and their optimal fusion scenario in each region. This way the complementary information of the individual feature...

متن کامل

استفاده از برآورد حالت‌های پویای دست مبتنی بر مدل، برای تقلید عملکرد بازوی انسان توسط ربات با داده‌های کینکت

Pose estimation is a process to identify how a human body and/or individual limbs are configured in a given scene. Hand pose estimation is an important research topic which has a variety of applications in human-computer interaction (HCI) scenarios, such as gesture recognition, animation synthesis and robot control. However, capturing the hand motion is quite a challenging task due to its high ...

متن کامل

MoDeep: A Deep Learning Framework Using Motion Features for Human Pose Estimation

In this work, we propose a novel and efficient method for articulated human pose estimation in videos using a convolutional network architecture, which incorporates both color and motion features. We propose a new human body pose dataset, FLIC-motion, that extends the FLIC dataset [1] with additional motion features. We apply our architecture to this dataset and report significantly better perf...

متن کامل

Siamese Regression Networks with Efficient mid-level Feature Extraction for 3D Object Pose Estimation

In this paper we tackle the problem of estimating the 3D pose of object instances, using convolutional neural networks. State of the art methods usually solve the challenging problem of regression in angle space indirectly, focusing on learning discriminative features that are later fed into a separate architecture for 3D pose estimation. In contrast, we propose an end-to-end learning framework...

متن کامل

Evaluation of Deep Learning based Pose Estimation for Sign Language

Human body pose estimation and hand detection being the prerequisites for sign language recognition(SLR), are both crucial and challenging tasks in Computer Vision and Machine Learning. There are many algorithms to accomplish these tasks for which the performance measures need to be evaluated for body posture recognition on a sign language dataset, that would serve as a baseline to provide impo...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

متن کامل
عنوان ژورنال:
  • Image Vision Comput.

دوره 19  شماره 

صفحات  -

تاریخ انتشار 2001