Shoichi Araki

Real-time tracking of multiple moving objects in moving camera image sequences using robust statistics

In this paper, we propose a new method for detection and tracking of moving objects from a moving camera image sequence using robust statistics and active contour models. We assume that the apparent background motion between two consecutive image frames can be approximated by affine transformation. In order to register the static background, we estimate affine transformation parameters using LMedS (least median of squares) method which is a kind of robust statistics. Split-and-merge contour models are employed for tracking multiple moving objects which have been recently proposed by the authors. Image energy of contour models is defined based on the image which is obtained by subtracting the previous frame transformed with estimated affine parameters from the current frame. We have implemented the method on an image processing system which consists of DSP boards for real-time tracking of moving objects from a moving camera image sequence.

Splitting of active contour models based on crossing detection for extraction of multiple objects

With previous active contour models (Snakes), separate extraction of multiple objects inside a contour was impossible, and thus the number of initial contours to be set was the same as that of objects. This paper aims at automatic extraction of multiple objects using Snakes, so that those objects can be extracted separately by means of a single initial contour that includes them all. For this purpose, a splitting contour model is proposed; specifically, a contraction-type Snake is split into multiple contours wherever self-crossing is detected during deformation by means of area term. With the proposed method, smaller contour models generated in splitting are extinguished, so that noise or nonrelevant tiny objects within the image are prevented from capturing; hence, stable extraction of objects is ensured even though the initial contour is placed well apart from the objects. Particularly, multiple objects may be extracted automatically with the initial contour set as the image border. Evaluation tests were carried out to prove the effectiveness of the proposed method, after which the method was applied successfully to actual images, namely, to extracting multiple cells from a microphotograph, and to extracting/tracing multiple objects from moving images.