We propose a novel background and foreground estimation algorithm in MAP-MRF approach for binarization of degraded document image. In the proposed algorithm, an assumption that background whiteness and foreground blackness is not employed differently from the conventional algorithm, and we employ character's irregularities based on local statistics. This makes the method possible to apply to the image with various colored characters, ex. outlined characters by colored background. The effectiveness and the validity are shown by applying the proposed method to various degraded document images.

The ball state tracking and detection technology plays a significant role in volleyball game analysis, whose performance is limited due to the challenges include: 1) the inaccurate ball trajectory; 2) multiple numbers of the ball event category; 3) the large intra-class difference of one event. With the goal of broadcasting supporting for volleyball games which requires a real time system, this paper proposes a ball state based parallel ball tracking and event detection method based on a sequential estimation method such as particle filter. This method employs a parallel process of the 3D ball tracking and the event detection so that it is friendly for real time system implementation. The 3D ball tracking process uses the same models with the past work [8]. For event detection process, a ball event change estimation based multiple system model, a past trajectory referred hit point likelihood and a court-line distance feature based event type detection are proposed. First, the multiple system model transits the ball event state, which consists the event starting time and the event type, through three models dealing with different ball motion situations in the volleyball game, such as the motion keeping and changing. The mixture of these models is decided by estimation of the ball event change estimation. Secondly, the past trajectory referred hit point likelihood avoids the processing time delay between the ball tracking and the event detection process by evaluating the probability of the ball being hit at certain time without using future ball trajectories. Third, the feature of the distance between the ball and the specific court line are extracted to detect the ball event type. Experimental results based on multi-view HDTV video sequences (2014 Inter High School Men's Volleyball Games, Japan), which contains 606 events in total, show that the detection rate reaches 88.61% while the success rate of 3D ball tracking keeps more than 99%.

Filtering and smoothing using a non-Gaussian state space model are proposed for motion trajectory of feature point in image sequence. A heavy-tailed non-Gaussian distribution is used for measurement noise to reduce the effect of outliers in motion trajectory. Experimental results are presented to show the usefulness of the proposed method.

Significant challenges in ball tracking of sports analysis by computer vision technology are: 1) accuracy of estimated 3D ball trajectory under difficult conditions; 2) external forces added by players lead to irregular motions of the ball; 3) unpredictable situations in the real game, i.e. the ball occluded by players and other objects, complex background and changing lighting condition. With the goal of multi-view 3D ball tracking, this paper proposes an abrupt motion adaptive system model, an anti-occlusion observation model, and a spatial density-based automatic recovery based on particle filter. The system model combines two different system noises that cover the motion of the ball both in general situation and situation subject to abrupt motion caused by external force. Combination ratio of these two noises and number of particles are adaptive to the estimated motion by weight distribution of particles. The anti-occlusion observation model evaluates image feature of each camera and eliminates influence of the camera with less confidence. The spatial density, which is calculated based on 3D ball candidates filtered out by spatial homographic relationship between cameras, is proposed for generating new set of particles to recover the tracking when tracking failure is detected. Experimental results based on HDTV video sequences (2014 Inter High School Men's Volleyball Games, Japan), which were captured by four cameras located at each corner of the court, show that the success rate achieved by the proposals of 3D ball tracking is 99.42%.