An image sensing device comprising: an input means for inputting image data including a moving image containing a plurality of frames; and a storage means for storing image data; further comprising: a first detection means for detecting, from the image data, a position of a specific part of a face in each of the frames; a second detection means for detecting feature points of the face from the image data on the basis of the detected position of the specific part and calculating vectors (c in Fig. 32) each having an initial point (3201 in Fig. 32) at a detected position of the specific part and an end point (3202 in Fig. 32) at a feature point to express the feature point by relative coordinates, in each of the frames; a determination means for determining a facial expression of the face on the basis of motion vectors (a in Fig. 33) of the feature points calculated by comparing vectors (b and c in Fig. 32 + 33) expressing the feature point by relative coordinates in adjacent frames (t, t + 1 in Fig. 32); and a register means for registering the input image data in said storage means when said determination means determines a predetermined facial expression; wherein said second detection means has higher detection accuracy than detection accuracy of said first detection means, and said first detection means is robust to a variation in a detection target, and wherein said determination means is adapted to automatically recognize facial expression in image data. an input means for inputting image data including a moving image containing a plurality of frames; and a storage means for storing image data; further comprising: a first detection means for detecting, from the image data, a position of a specific part of a face in each of the frames; a second detection means for detecting feature points of the face from the image data on the basis of the detected position of the specific part and calculating vectors (c in Fig. 32) each having an initial point (3201 in Fig. 32) at a detected position of the specific part and an end point (3202 in Fig. 32) at a feature point to express the feature point by relative coordinates, in each of the frames; a determination means for determining a facial expression of the face on the basis of motion vectors (a in Fig. 33) of the feature points calculated by comparing vectors (b and c in Fig. 32 + 33) expressing the feature point by relative coordinates in adjacent frames (t, t + 1 in Fig. 32); and a register means for registering the input image data in said storage means when said determination means determines a predetermined facial expression; wherein said second detection means has higher detection accuracy than detection accuracy of said first detection means, and said first detection means is robust to a variation in a detection target, and wherein said determination means is adapted to automatically recognize facial expression in image data. a first detection means for detecting, from the image data, a position of a specific part of a face in each of the frames; a second detection means for detecting feature points of the face from the image data on the basis of the detected position of the specific part and calculating vectors (c in Fig. 32) each having an initial point (3201 in Fig. 32) at a detected position of the specific part and an end point (3202 in Fig. 32) at a feature point to express the feature point by relative coordinates, in each of the frames; a determination means for determining a facial expression of the face on the basis of motion vectors (a in Fig. 33) of the feature points calculated by comparing vectors (b and c in Fig. 32 + 33) expressing the feature point by relative coordinates in adjacent frames (t, t + 1 in Fig. 32); and a register means for registering the input image data in said storage means when said determination means determines a predetermined facial expression; wherein said second detection means has higher detection accuracy than detection accuracy of said first detection means, and said first detection means is robust to a variation in a detection target, and wherein said determination means is adapted to automatically recognize facial expression in image data.