Visual tracking plays an important role in various robotic tasks. We have developed a view based visual tracking system to cope with change of the appearance of the template in a 3D environment using affine transformed templates. In view-based visual tracking, however, there are still critical situations in which the tracking fails because of occlusion by general objects and/or human hand in the environment, particularly in cases where humans and robots perform cooperative handling of objects. This paper presents two methods to cope with such occlusion problems. The first method, which we call tessellated template method, detects the occlusion based on an evaluation of correlation errors in a tessellated template. The second method deals with occlusion caused by human hand and we use infrared images to detect the occluded region in the target template. The system then creates a mask of the occluded region and eliminates pixels in the mask from calculating correlation with the template image. In the prototype system, the generation of the mask and the correlation can be performed, typically, in one or two TV frame. We have integrated the proposed methods into the view-based visual tracking system which we have already developed. Experimental results demonstrate the usefulness of the proposed methods.