Ryusuke Miyamoto

Pedestrian recognition in far-infrared images by combining boosting-based detection and skeleton-based stochastic tracking

Nowadays, pedestrian recognition in far-infrared images toward realizing a night vision system becomes a hot topic. However, sufficient performance could not be achieved by conventional schemes for pedestrian recognition in far-infrared images. Since the properties of far-infrared images are different from visible images, it is not known what kind of scheme is suitable for pedestrian recognition in far-infrared images. In this paper, a novel pedestrian recognition scheme combining boosting-based detection and skeleton-based stochastic tracking suitable for recognition in far-infrared images is proposed. Experimental results by using far-infrared sequences show the proposed scheme achieves highly accurate pedestrian recognition by combining accurate detection with few false positives and accurate tracking.

Probabilistic Pedestrian Tracking Based on a Skeleton Model

A novel pedestrian tracking scheme based on a particle filter is proposed, which adopts a skeleton model of a pedestrian as a state space model and uses distance transformed images for likelihood estimation. The six-stick skeleton model used in the proposed approach is very distinctive in representing a pedestrian simply but effectively, with which the efficient state space for the pedestrian tracking can be derived. Experimental results by using PETS sample sequences demonstrate that the proposed approach achieves highly accurate pedestrian tracking without any of prior learning.

Stochastic Pedestrian Tracking Based on 6-Stick Skeleton Model

A novel pedestrian tracking scheme based on a particle filter is proposed, which adopts a skeleton model of a pedestrian for a state space model and distance transformed images for likelihood computation. The 6-stick skeleton model used in the proposed approach is very distinctive in representing a pedestrian simply but effectively. By the experiment using the real sequences provided by PETS, it is shown that the target pedestrian is tracked adequately by the proposed approach with a simple silhouette extraction method which consists of only background subtraction, even if the tracking target moves so complicatedly and is often so cluttered by other obstacles that the pedestrian can not be tracked by the conventional methods. Moreover, it is demonstrated that the proposed scheme can track the multiple targets in the complex case that their trajectories intersect.

High quality Motion JPEG2000 coding scheme based on the human visual system

A novel high quality Motion JPEG2000 coding scheme is proposed, which is based on the human visual system being insensitive to the high frequency components of an image. This method enhances subjective video quality by controlling the amount of data allocated to each code-block according to the extent of its motion. The proposed method enables video coding without degrading the subjective quality of the existing method at lower bitrate.

Video quality enhancement for Motion JPEG2000 encoding based on the human visual system

A novel Motion JPEG2000 encoding method is proposed, which is based on the human visual system being insensitive to high frequency component of image. This method enhances subjective video quality by controlling bitrate of each region, such as a tile or a code-block, or each wavelet coefficient according to its amount of motion. The proposed method can encode video streams whose subjective quality is the same as that by existing method at lower bitrate.