This paper presents a novel adversarial deep neural network to estimate human poses from still images, such as those obtained from CCTV and Internet of Things (IoT) devices. Specifically, the proposed adversarial deep neural network exhibits the spatial hierarchy of human body parts considering the fact that predicting the position of some parts are more challenging than others. The generative and the discriminate portions of the proposed adversarial deep neural network are designed to encode the spatial relationship between the parts in the first stage of the hierarchy (parents) and the parts in the second stage of the hierarchy (children). Each of the generator and the discriminator networks is designed as two components, which are sequentially connected together to infer rich appearance potentials and to encode not only the likelihood of the part’s existence but also the relationships between each body part and its parent.The method is evaluated on three different data sets, whose findings suggest that the proposed network achieves comparable results with other competing state-of-the-art approaches.
To View the Base Paper Abstract Contents
Now it is Your Time to Shine.
Great careers Start Here.
We Guide you to Every Step
Success! You're Awesome
Thank you for filling out your information!
We’ve sent you an email with your Final Year Project PPT file download link at the email address you provided. Please enjoy, and let us know if there’s anything else we can help you with.
To know more details Call 900 31 31 555
The WISEN Team